Tissues are heterogeneous ecosystems comprised of various cell types. For example, in tumor tissues, malignant cancer cells are surround by various non-malignant stromal cells. Proteins, especially N-linked glycoproteins, are key players in tumor microenvironment and respond to many extracellular stimuli for involving and regulating intercellular signaling. Understanding the human proteome and glycoproteome in heterogeneous tissues with spatial resolution are meaningful for exploring intercellular signaling networks and discovering protein biomarkers for various diseases, such as cancer. In this study, we aimed to develop new liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based analytical methods for spatially-resolved proteome and glycoproteome profiling in tissue samples, and apply them for profiling potential biomarkers for pancreatic cancer. We first systematically and synchronously optimized the LC-MS parameters to increase peptide sequencing efficiency in data dependent proteomics. Taking advantage of its hybrid instrument design with various mass analyzer and fragmentation strageties, the Orbitrap Fusion mass spectrometer was used for systematically comparing the popular high-high approach by using orbitrap for both MS1 and MS2 scans and high-low approach by using orbitrap for MS1 scan and ion trap for MS2 scans. High-high approach outperformed high-low approach in terms of better saturation of the scan cycle and higher MS2 identification rate. We then systematically optimized various MS parameters for high-high approach. We investigated the influence of isolation window and injection time on scan speed and MS2 identification rate. We then explored how to properly set dynamic exclusion time according to the chromatography peak width. Furthermore, we found that the orbitrap analyzer, rather than the analytical column, was easily saturated with higher peptide loading amount, thus limited the dynamic range of MS1-based quantification. Finally, by using the optimized LC-MS parameters, more than 9000 proteins and 110,000 unique peptides were identified by using 10 hours of effective LC gradient time. The study therefore illustrated the importance of synchronizing LC-MS precursor targeting and high-resolution fragment detection for high-efficient data dependent proteomics. Understanding the tumor heterogeneity through spatially resolved proteome profiling is meaningful for biomedical research. Laser capture microdissection (LCM) is a powerful technology for exploring local cell populations without losing spatial information. Here, we designed an immunohistochemistry (IHC)-based workflow for cell type-resolved proteome analysis of tissue samples. Firstly, targeted cell type was stained by IHC using antibody targeting cell-type specific marker to improve accuracy and efficiency of LCM. Secondly, to increase protein recovery from chemically crosslinked IHC tissues, we optimized a decrosslinking procedure to seamlessly combine with the integrated spintip-based sample preparation technology SISPROT. This newly developed approach, termed IHC-SISPROT, has comparable performance with traditional H&E staining-based proteomic analysis. High sensitivity and reproducibility of IHC-SISPROT was achieved by combining with data independent proteomic analysis. This IHC-SISPROT workflow was successfully applied for identifying 6660 and 6052 protein groups from cancer cells and cancer- associated fibroblasts (CAFs) by using only 5 mm 2 and 12 μm thickness of hepatocellular carcinoma tissue section. Bioinformatic analysis revealed the enrichment of cell type-specific ligands and receptors and potentially new communications between cancer cells and CAFs by these signaling proteins. Therefore, IHC-SISPROT is sensitive and accurate proteomic approach for spatial profiling of cell type-specific proteome from tissues. N-linked glycoproteins are promising candidates for diagnostic and prognostic biomarkers and therapeutic targets. They often locate at plasma membrane and extracellular space with distinct cell type distribution in tissue microenvironment. Due to access to only low microgram of proteins and low abundance of glycoproteins in tissue sections harvested by LCM, region- and cell type-resolved glycoproteome analysis of tissue sections remains challenging. Here we designed a fully integrated spintip-based glycoproteomic approach (FISGlyco) which achieved all the steps for glycoprotein enrichment, digestion, deglycosylation and desalting in a single spintip device. Sample loss is significantly reduced and the total processing time is reduced to 4 hours, while detection sensitivity and label-free quantification precision is greatly improved. 607 N-glycosylation sites were successfully identified and quantified from only 5 μg of mouse brain proteins. By seamlessly combining with LCM, the first region-resolved N-glycoproteome profiling of four mouse brain regions, including isocortex, hippocampus, thalamus, and hypothalamus, was achieved, with 1,875, 1,794, 1,801, and 1,417 N-glycosites identified, respectively. Our approach could be a generic approach for region and even cell type specific glycoproteome analysis of tissue sections. Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with five year survival rate of around 8%. No effective biomarkers and targeted therapy are one of the major reasons for this urgent clinical situation. To explore potential protein biomarkers and drug targets located at intercellular space of pancreatic tumor microenvironment, we established chemical proteomic approach for deep glycoproteome profiling of PDAC clinical tissue samples based on the above- mentioned new proteomic methods. Taking advantage of a long chain biotin- hydrazide probe with less space hindrance, the new method outperformed traditional hydrazide chemistry method in terms of sensitivity, time efficiency and glycoproteome coverage. The method was successfully applied to enrich and validate LIF and its receptors as potential biomarkers for PDAC. In addition, to explore the full map of pancreatic tumor microenvironment glycoproteome with diagnostic and therapeutic values, we collected 114 pancreatic tissues, including 30 PDAC tumor tissues, 30 adjacent non-tumor (NT) tissues, 32 chronic pancreatitis tissues and 22 normal pancreatic tissues, and systematically profiled their glycoprotein expression pattern by using the developed glycoproteomic strategy. The deepest glycoproteome of PDAC was achieved, which covered the majority of previously reported glycoprotein biomarkers and drug targets for PDAC. Importantly, we discovered many new glycoproteins with differential expression in PDAC and normal tissue types. Moreover, LCM-based cell-type proteome profiling was achieved for 13 PDAC tissue samples, which covered more than 8000 proteins for both pancreatic stromal cells and pancreatic cancer cells in each sample. We therefore provided a valuable resource for screening novel and cancer specific glycoprotein biomarkers for pancreatic cancer with spatial resolution

Esophageal cancer and lung cancer are among the most common cancers worldwide with millions of new cases annually. Esophageal cancer patients at an advanced stage suffer from a poor five-year survival rate. However, only fewer than 30% of esophageal cancer cases were diagnosed at an early stage. For lung cancer, malignant pleural effusion (MPE) is an important hallmark for late-stage patients with metastasis. However, other causes of pleural effusions including tuberculosis bring difficulties in the diagnosis of MPE. It is necessary to develop novel diagnostic biomarkers and elucidate the pathological mechanism of esophageal cancer and lung cancer. Metabolic reprogramming is an emerging hallmark of cancer. It has been clear that metabolites play a critical role in cancer development and impose vulnerabilities that could be targeted for cancer therapy. The overall objective of this study is to comprehensively characterize the metabolic dysregulation in esophageal cancer and lung cancer for biomarker discovery and pathological elucidation, by using liquid chromatography--mass spectrometry (LC-MS)-based metabolomics and lipidomics. Paired tumors and normal adjacent tissues from esophageal squamous-cell carcinoma (ESCC) patients were first analyzed through global metabolomic and lipidomic profiling. Tumors were clearly separated from the normal tissues based on the partial least-square discriminant analysis (PLS-DA) model (R2Y >0.85 and Q2Y >0.79 in metabolomic profiling and R2Y >0.70 and Q2Y >0.67 in lipidomic profiling). A preliminary list of 41 polar metabolites and 65 lipids were identified to be significantly perturbed in tumor tissues. Kynurenine, spermidine, citicoline, as well as several glucosylceramides and phosphatidylcholines (PC) showed excellent predictive potential with area under curve (AUC) values better than 0.95 in receiver operating characteristic (ROC) models. Major elevated metabolic pathways were polyamine biosynthesis, glycerophospholipid metabolism, methionine mechanism, arginine and proline mechanism, and kynurenine metabolism, suggesting active amino acid biosynthesis and lipid biosynthesis in ESCC. The potential biomarkers and dysregulated pathways discovered above in ESCC tissue was further validated using targeted metabolomic, lipidomic and proteomic profiling. Polyamine biosynthesis was found to be activated in ESCC through the overexpression of tumor promoting ornithine decarboxylase and spermidine/spermine synthases. Upregulated levels of S-adenosylmethionine and DNA (cytosine-5)-methyltransferase 1 implied DNA hypermethylation in ESCC. Elevated purines in tumors were generated through the overexpression of methylenetetrahydrofolate dehydrogenases. Active phospholipid biosynthesis in tumors was promoted by overexpression of choline transporters and synthase of citicoline, which may accelerate the tumor growth. Dysregulation of coenzyme A species with different fatty acyl chains showed the same trend as of phospholipids, implying the specific activation of relevant acyltransferases in the phospholipid remodeling pathway. Moreover, essential amino acids exhibited a higher upregulation trends in patients with high-grade tumor or with cancer recurrence. Collectively, this study revealed the detailed metabolic dysregulations in ESCC tumor tissues, discovered potential metabolite biomarkers and identified therapeutic targets of ESCC. In order to explore the clinical application of the discovered biomarkers, metabolomic and lipidomic profiling was further performed on ESCC plasma samples. Eight metabolites were found to be simultaneously upregulated in ESCC tumors and plasma samples, indicating their potential as tumor-derived plasma biomarkers. Among them, a panel of five tumor-derived plasma biomarkers consisting of arginine, acetylspermidine, methylguanosine, dimethylguanosine and cystine showed good diagnostic potential in the cross validation. These biomarkers are related with polyamine biosynthesis and purine metabolism, which are critical to support tumor growth. For lung cancer, MPE from lung adenocarcinoma patients were investigated by LC-MS/MS-based metabolomic and lipidomic profiling. In PLS-DA models, the MPE samples were clearly separated from benign pleural effusion samples from pulmonary tuberculosis patients. A group of 17 polar metabolites and 45 lipids were identified to be significantly perturbed in MPE. For diagnostic purposes, ether lipid biomarkers, including PCs, lyso-PCs and phosphatidylethanolamines, showed an excellent predictive ability with the highest AUC value of 0.953 in ROC models. Furthermore, downregulated ether lipids and upregulated oxidized polyunsaturated fatty acids in MPE reflected the elevated oxidative stress and peroxisome disorder in lung cancer patients, which offers deeper understanding in lung cancer pathology.

Esophageal cancer and lung cancer are among the most common cancers worldwide with millions of new cases annually. Esophageal cancer patients at an advanced stage suffer from a poor five-year survival rate. However, only fewer than 30% of esophageal cancer cases were diagnosed at an early stage. For lung cancer, malignant pleural effusion (MPE) is an important hallmark for late-stage patients with metastasis. However, other causes of pleural effusions including tuberculosis bring difficulties in the diagnosis of MPE. It is necessary to develop novel diagnostic biomarkers and elucidate the pathological mechanism of esophageal cancer and lung cancer. Metabolic reprogramming is an emerging hallmark of cancer. It has been clear that metabolites play a critical role in cancer development and impose vulnerabilities that could be targeted for cancer therapy. The overall objective of this study is to comprehensively characterize the metabolic dysregulation in esophageal cancer and lung cancer for biomarker discovery and pathological elucidation, by using liquid chromatography--mass spectrometry (LC-MS)-based metabolomics and lipidomics. Paired tumors and normal adjacent tissues from esophageal squamous-cell carcinoma (ESCC) patients were first analyzed through global metabolomic and lipidomic profiling. Tumors were clearly separated from the normal tissues based on the partial least-square discriminant analysis (PLS-DA) model (R2Y >0.85 and Q2Y >0.79 in metabolomic profiling and R2Y >0.70 and Q2Y >0.67 in lipidomic profiling). A preliminary list of 41 polar metabolites and 65 lipids were identified to be significantly perturbed in tumor tissues. Kynurenine, spermidine, citicoline, as well as several glucosylceramides and phosphatidylcholines (PC) showed excellent predictive potential with area under curve (AUC) values better than 0.95 in receiver operating characteristic (ROC) models. Major elevated metabolic pathways were polyamine biosynthesis, glycerophospholipid metabolism, methionine mechanism, arginine and proline mechanism, and kynurenine metabolism, suggesting active amino acid biosynthesis and lipid biosynthesis in ESCC. The potential biomarkers and dysregulated pathways discovered above in ESCC tissue was further validated using targeted metabolomic, lipidomic and proteomic profiling. Polyamine biosynthesis was found to be activated in ESCC through the overexpression of tumor promoting ornithine decarboxylase and spermidine/spermine synthases. Upregulated levels of S-adenosylmethionine and DNA (cytosine-5)-methyltransferase 1 implied DNA hypermethylation in ESCC. Elevated purines in tumors were generated through the overexpression of methylenetetrahydrofolate dehydrogenases. Active phospholipid biosynthesis in tumors was promoted by overexpression of choline transporters and synthase of citicoline, which may accelerate the tumor growth. Dysregulation of coenzyme A species with different fatty acyl chains showed the same trend as of phospholipids, implying the specific activation of relevant acyltransferases in the phospholipid remodeling pathway. Moreover, essential amino acids exhibited a higher upregulation trends in patients with high-grade tumor or with cancer recurrence. Collectively, this study revealed the detailed metabolic dysregulations in ESCC tumor tissues, discovered potential metabolite biomarkers and identified therapeutic targets of ESCC. In order to explore the clinical application of the discovered biomarkers, metabolomic and lipidomic profiling was further performed on ESCC plasma samples. Eight metabolites were found to be simultaneously upregulated in ESCC tumors and plasma samples, indicating their potential as tumor-derived plasma biomarkers. Among them, a panel of five tumor-derived plasma biomarkers consisting of arginine, acetylspermidine, methylguanosine, dimethylguanosine and cystine showed good diagnostic potential in the cross validation. These biomarkers are related with polyamine biosynthesis and purine metabolism, which are critical to support tumor growth. For lung cancer, MPE from lung adenocarcinoma patients were investigated by LC-MS/MS-based metabolomic and lipidomic profiling. In PLS-DA models, the MPE samples were clearly separated from benign pleural effusion samples from pulmonary tuberculosis patients. A group of 17 polar metabolites and 45 lipids were identified to be significantly perturbed in MPE. For diagnostic purposes, ether lipid biomarkers, including PCs, lyso-PCs and phosphatidylethanolamines, showed an excellent predictive ability with the highest AUC value of 0.953 in ROC models. Furthermore, downregulated ether lipids and upregulated oxidized polyunsaturated fatty acids in MPE reflected the elevated oxidative stress and peroxisome disorder in lung cancer patients, which offers deeper understanding in lung cancer pathology.

Organochlorines are ubiquitous pollutants of the marine environment. These lipid-soluble and highly persistent compounds are found in detectable amounts in almost all marine organisms, and accumulate in the lipid tissues of marine animals. This bioaccumulation leads to biomagnification of these contaminants in higher trophic levels. Near the top of many marine food chains are found the marine mammals, in whose blubber high levels of organochlorine residues have been measured. The most commonly occurring of these pollutants in these animals are the polychlorinated biphenyls (PCB's) and p,p-DDE, a metabolite of the insecticide DDT. These substances have been shown to cause disruptions in the endocrine, immune, and reproductive systems, and are passed from mother to offspring through the placenta and by lactation. Presence and levels of residues of these compounds are, therefore, monitored in marine mammals to provide an indication of the health of a given population and the environment in which they live. Such monitoring is generally done with the use of gas chromatography (GC). High performance liquid chromatography (HPLC) is little used due to the poor ultraviolet (UV) absorbance properties of many of the organochlorines. PCB's and p,p-DDE do absorb UV well enough at concentrations usually encountered in marine mammals to permit the use of HPLC for detection and semiquantification of these substances. A method was developed for the screening of blubber of marine mammals for total PCB's and p,p-DDE using HPLC. The method was applied to the detection and approximation of levels of these two organochlorines in marine mammals from the east and west coasts of the United States. Geographical differences in levels of the two pollutants were found, indicating differences in primary feeding ranges. Evidence of placental transfer of these two organochlorines was also found. Especially high residue levels were found in the blubber of stranded killer whales, indicating that acquisition of high pollutant burdens is still a problem in these top predators. It was concluded that HPLC can be used to screen marine mammals for PCB's and p,p-DDE, and that residue levels determined can be useful in investigating species range, pollutant burdens, and health of populations.

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