Mass spectrometry‐based secretome analysis of non‐small cell lung cancer cell lines

Tyrosine kinase inhibitors, such as erlotinib, display reliable responses and survival benefits for the treatment of human non‐small cell lung cancer (NSCLC) patients. However, primary or acquired resistance limits their therapeutic success. In this study, we conducted in‐depth mass spectrometric analyses of NSCLC cell secretomes. To identify secreted proteins that are differentially regulated in erlotinib‐sensitive (PC‐9) and ‐resistant (PC‐9ER) NSCLC cell lines, SILAC experiments were performed. On average, 900 proteins were identified in each sample with low variations in the numbers of identified proteins. Fourteen proteins were found to be differently regulated among erlotinib‐sensitive and ‐resistant NSCLC cell lines, with five proteins (tissue‐type plasminogen activator, epidermal growth factor receptor, urokinase‐type plasminogen activator, platelet‐derived growth factor D, and myeloid‐derived growth factor) showing the most prominent regulation. Tissue‐type plasminogen activator (t‐PA) was up to 10‐times upregulated in erlotinib‐resistant NSCLC cells compared with erlotinib‐sensitive cells. T‐PA is an established tumor marker for various cancer types and seems to be a promising prognostic marker to differentiate erlotinib‐sensitive from erlotinib‐resistant NSCLC cells. To gain further insights into t‐PA‐regulated pathways, a t‐PA variant was expressed in E. coli cells and its interactions with proteins secreted from erlotinib‐sensitive and ‐resistant NCSLC cells were studied by a combined affinity enrichment chemical cross‐linking/mass spectrometry (MS) approach. Fourteen proteins were identified as potential t‐PA interaction partners, deserving a closer inspection to unravel the mechanisms underlying erlotinib resistance in NSCLC cells.     

Proteomic analysis of mouse astrocytes and their secretome by a combination of FASP and StageTip‐based,high pH,reversed‐phase fractionation

Astrocytes are the most abundant cells in the CNS, but their function remains largely unknown. Characterization of the whole‐cell proteome and secretome in astrocytes would facilitate the study of their functions in various neurodegenerative diseases and astrocyte–neuron communication. To build a reference proteome, we established a C8‐D1A astrocyte proteome to a depth of 7265 unique protein groups using a novel strategy that combined two‐step digestion, filter‐aided sample preparation, StageTip‐based high pH fractionation, and high‐resolution MS. Nearly, 6000 unique protein groups were identified from conditioned media of astrocyte cultures, constituting the largest astrocyte secretome that has been reported. High‐confidence whole‐cell proteomes and secretomes are valuable resources in studying astrocyte function by label‐free quantitation and bioinformatics analysis. All MS data have been deposited in the ProteomeXchange with identifier PXD000501 ( http://proteomecentral.proteomexchange.org/dataset/PXD000501 ).     

Glucosyltransferase‐dependent and ‐independent effects of TcdB on the proteome of HEp‐2 cells

Toxin B (TcdB) of the nosocomial pathogen C. difficile has been reported to exhibit a glucosyltransferase‐dependent and ‐independent effect on treated HEp‐2 cells at toxin concentration above 0.3 nM. In order to investigate and further characterize both effects epithelial cells were treated with wild type TcdB and glucosyltransferase‐deficient TcdB_NXN and their proteomes were analyzed by LC‐MS. Triplex SILAC labeling was used for quantification. Identification of 5212 and quantification of 4712 protein groups was achieved. Out of these 257 were affected by TcdB treatment, 92 by TcdB_NXN treatment and 49 by both. TcdB mainly led to changes in proteins that are related to “GTPase mediated signaling” and the “cytoskeleton” while “chromatin” and “cell cycle” related proteins were altered by both, TcdB and TcdB_NXN. The obtained dataset of HEp‐2 cell proteome helps us to better understand glucosyltransferase‐dependent and ‐independent mechanisms of TcdB and TcdB_NXN, particularly those involved in pyknotic cell death. All proteomics data have been deposited in the ProteomeXchange with the dataset identifier PXD006658 ( https://proteomecentral.proteomexchange.org/dataset/PXD006658 ).     

Qualitative and quantitative analysis of the adult Drosophila melanogaster proteome

Drosophila melanogaster is one of the most widely used model organisms in life sciences. Mapping its proteome is of great significance for understanding the biological characteristics and tissue functions of this species. However, the comprehensive coverage of its proteome remains a challenge. Here, we describe a high‐coverage analysis of whole fly through a 1D gel electrophoresis and LC‐MS/MS approach. By combining the datasets of two types of SDS‐PAGE and two kinds of tagmata, the high‐coverage analysis resulted in the identification of 5262 genes, which correspond to 38.23% of the entire coding genes. Moreover, we found that the fly head and body have different molecular weight distributions of their proteomes when the proteins were resolved with SDS‐PAGE and image analysis of the stained gel. This phenomenon was further confirmed by both label‐free and isobaric tags for relative and absolute quantitation‐based quantitative approaches. The consistent results of the two different quantitation methods also demonstrated the stability and accuracy of the LC‐MS/MS platform. The MS proteomics data have been deposited to the ProteomeXchange with identifiers PXD000454 and PXD000455 ( http://proteomecentral.proteomexchange.org/dataset/PXD000454 ; ( http://proteomecentral.proteomexchange.org/dataset/PXD000455 ).     

UHRF1 predicts poor prognosis by triggering cell cycle in lung adenocarcinoma

Accumulating evidence suggests that ubiquitin‐like with plant homeodomain and ring finger domains 1 (UHRF1) is overexpressed in non‐small cell lung cancer (NSCLC); however, the expression and function of UHRF1 in the subtype of NSCLC are still unclear. Here, we investigate the expression and prognosis traits of UHRF1 in large NSCLC cohorts and explore the molecular characters during UHRF1 up‐regulation. We find that UHRF1 is predominantly overexpressed in lung squamous cell carcinoma (SCC). Surprisingly, the up‐regulated UHRF1 is only associated with the overall survival of lung adenocarcinoma (ADC) and knockdown of UHRF1 dramatically attenuates ADC tumorigenesis. Mechanically, we identify a hub gene that includes a total of 55 UHRF1‐related genes, which are tightly associated with cell cycle pathway and yield to the poor clinical outcome in ADC patients. What's more, we observe knockdown of UHRF1 only affects ADC cells cycle and induces cell apoptosis. These results suggest that up‐regulated UHRF1 only contributes to lung ADC survival by triggering cell cycle pathway, and it may be a prognostic biomarker for lung ADC patients.     

In‐depth protein profiling of the postsynaptic density from mouse hippocampus using data‐independent acquisition proteomics

Located at neuronal terminals, the postsynaptic density (PSD) is a highly complex network of cytoskeletal scaffolding and signaling proteins responsible for the transduction and modulation of glutamatergic signaling between neurons. Using ion‐mobility enhanced data‐independent label‐free LC‐MS/MS, we established a reference proteome of crude synaptosomes, synaptic junctions, and PSD derived from mouse hippocampus including TOP3‐based absolute quantification values for identified proteins. The final dataset across all fractions comprised 49 491 peptides corresponding to 4558 protein groups. Of these, 2102 protein groups were identified in highly purified PSD in at least two biological replicates. Identified proteins play pivotal roles in neurological and synaptic processes providing a rich resource for studies on hippocampal PSD function as well as on the pathogenesis of neuropsychiatric disorders. All MS data have been deposited in the ProteomeXchange with identifier PXD000590 ( http://proteomecentral.proteomexchange.org/dataset/PXD000590 ).     

Long non‐coding RNA SNHG15 promotes CDK14 expression via miR‐486 to accelerate non‐small cell lung cancer cells progression and metastasis

Long non‐coding RNAs (lncRNAs) have been validated to play important role in multiple cancers, including non‐small cell lung cancer (NSCLC). In present study, our team investigate the biologic role of SNHG15 in the NSCLC tumorigenesis. LncRNA SNHG15 was significantly upregulated in NSCLC tissue samples and cells, and its overexpression was associated with poor prognosis of NSCLC patients. In vitro, loss‐of‐functional cellular experiments showed that SNHG15 silencing significantly inhibited the proliferation, promoted the apoptosis, and induced the cycle arrest at G0//G1 phase. In vivo, xenograft assay showed that SNHG15 silencing suppressed tumor growth of NSCLC cells. Besides, SNHG15 silencing decreased CDK14 protein expression both in vivo and vitro. Bioinformatics tools and luciferase reporter assay confirmed that miR‐486 both targeted the 3′‐UTR of SNHG15 and CDK14 and was negatively correlated with their expression levels. In summary, our study conclude that the ectopic overexpression of SNHG15 contribute to the NSCLC tumorigenesis by regulating CDK14 protein via sponging miR‐486, providing a novel insight for NSCLC pathogenesis and potential therapeutic strategy for NSCLC patients.     

Absolute protein quantification allows differentiation of cell‐specific metabolic routes and functions

Total protein approach (TPA) is a proteomic method that allows calculation of concentrations of individual proteins and groups of functionally related proteins in any protein mixture without spike‐in standards. Using the two‐step digestion–filter‐aided sample preparation method and LC‐MS/MS analysis, we generated comprehensive quantitative datasets of mouse intestinal mucosa, liver, red muscle fibers, brain, and of human plasma, erythrocytes, and tumor cells lines. We show that the TPA‐based quantitative data reflect well‐defined and specific physiological functions of different organs and cells, for example nutrient absorption and transport in intestine, amino acid catabolism and bile secretion in liver, and contraction of muscle fibers. Focusing on key metabolic processes, we compared metabolic capacities in different tissues and cells. In addition, we demonstrate quantitative differences in the mitochondrial proteomes. Providing insight into the abundances of mitochondrial metabolite transporters, we demonstrate that their titers are well tuned to cell‐specific metabolic requirements. This study provides for the first time a comprehensive overview of the protein hardware mediating metabolism in different mammalian organs and cells. The presented approach can be applied to any other system to study biological processes. All MS data have been deposited in the ProteomeXchange with identifier PXD001352 ( http://proteomecentral.proteomexchange.org/dataset/PXD001352 ).     

Unique Protein Profiles of Extracellular Vesicles as Diagnostic Biomarkers for Early and Advanced Non‐Small Cell Lung Cancer

Extracellular vesicles (EVs) mediate intercellular communication via transferring proteins and other biological molecules and have been recently investigated as biomarkers of disease. Sensitive and specific biomarkers are required for lung cancer diagnosis and prognosis. The present study screens for abnormal EV proteins in non‐small cell lung cancer (NSCLC) using a quantitative proteomics strategy involving LC‐MS/MS to identify ideal biomarkers for NSCLC diagnosis. EVs are enriched from the sera of early and advanced NSCLC patients and healthy controls and from cell culture supernatants of lung adenocarcinoma and bronchial epithelial cell lines. In the sera and supernatants, 279 and 632 differentially expressed proteins, respectively, are associated with signaling pathways including extracellular membrane–receptor interaction, focal adhesion, and regulation of the actin cytoskeleton. Thirty‐two EV proteins are identified at the intersection of differentially expressed proteins between the NSCLC groups and cell lines. Based on bioinformatics analysis, in silico immunohistochemical, and PRM verification, fibronectin is selected for following in vitro studies and validation with an independent cohort. Fibronectin on EVs is estimated to perform well in the diagnosis of NSCLC patients based on AUC, showing great potential for clinical use and demonstrating the efficacy of this method for EV‐associated biomarker screening.     

Dickkopf‐1‐promoted vasculogenic mimicry in non‐small cell lung cancer is associated with EMT and development of a cancer stem‐like cell phenotype

To characterize the contributions of Dickkopf‐1 (DKK1) towards the induction of vasculogenic mimicry (VM) in non‐small cell lung cancer (NSCLC), we evaluated cohorts of primary tumours, performed in vitro functional studies and generated xenograft mouse models. Vasculogenic mimicry was observed in 28 of 205 NSCLC tumours, while DKK1 was detected in 133 cases. Notably, DKK1 was positively associated with VM. Statistical analysis showed that VM and DKK1 were both related to aggressive clinical course and thus were indicators of a poor prognosis. Moreover, expression of epithelial‐mesenchymal transition (EMT)‐related proteins (vimentin, Slug, and Twist), cancer stem‐like cell (CSC)‐related proteins (nestin and CD44), VM‐related proteins (MMP2, MMP9, and vascular endothelial‐cadherin), and β‐catenin‐nu were all elevated in VM‐positive and DKK1‐positive tumours, whereas the epithelial marker (E‐cadherin) was reduced in the VM‐positive and DKK1‐positive groups. Non‐small cell lung cancer cell lines with overexpressed or silenced DKK1 highlighted its role in the restoration of mesenchymal phenotypes and development of CSC characteristics. Moreover, DKK1 significantly promotes NSCLC tumour cells to migrate, invade and proliferate. In vivo animal studies demonstrated that DKK1 enhances the growth of transplanted human tumours cells, as well as increased VM formation, mesenthymal phenotypes and CSC properties. Our results suggest that DKK1 can promote VM formation via induction of the expression of EMT and CSC‐related proteins. As such, we feel that DKK1 may represent a novel target of NSCLC therapy.     

Clinical relevance and functional implications for human leucocyte antigen‐g expression in non‐small‐cell lung cancer

HLA‐G has been documented both in establishment of anti‐tumour immune responses and in tumour evasion. To investigate the clinical relevance of HLA‐G in non‐small‐cell lung cancer (NSCLC), expression status and potential significance of HLA‐G in NSCLC were analysed. In this study, HLA‐G expression in 101 NSCLC primary lesions and plasma soluble HLA‐G (sHLA‐G) from 91 patients were analysed with immunohistochemistry and ELISA, respectively. Correlations between HLA‐G status and various clinical parameters including survival time were evaluated. Meanwhile, functional analysis of transfected cell surface HLA‐G expression and plasma sHLA‐G form NSCLC patients on natural killer (NK) cell cytolysis were performed. Data revealed that HLA‐G was expressed in 41.6% (42/101) NSCLC primary lesions, while undetectable in adjacent normal lung tissues. HLA‐G expression in NSCLC lesions was strongly correlated to disease stages (P= 0.002). Plasma sHLA‐G from NSCLC patients was markedly higher than that in normal controls (P= 0.004), which was significantly associated with the disease stages (I versus IV, P= 0.025; II versus IV, P= 0.029). Patient plasma sHLA‐G level (≥median, 32.0 U/ml) had a significantly shorter survival time (P= 0.044); however, no similar significance was observed for the lesion HLA‐G expression. In vitro data showed that both cell surface HLA‐G and patient plasma sHLA‐G could dramatically decrease the NK cell cytolysis. Our findings indicated that both lesion HLA‐G expression and plasma sHLA‐G in NSCLC is related to the disease stage and can exert immunosuppression to the NK cell cytolysis, indicating that HLA‐G could be a potential therapeutic target. Moreover, plasma sHLA‐G in NSCLC patients could be used as a prognosis factor for NSCLC.     

Characterization of a SILAC method for proteomic analysis of primary rat microglia

Microglia play important and dynamic roles in mediating a variety of physiological and pathological processes during the development, normal function and degeneration of the central nervous system. Application of SILAC‐based proteomic analysis would greatly facilitate the identification of cellular pathways regulating the multifaceted phenotypes of microglia. We and others have successfully SILAC‐labeled immortalized murine microglial cell lines in previous studies. In this study, we report the development and evaluation of a SILAC‐labeled primary rat microglia model. Although the isotope labeling scheme for primary microglia is drastically different from that of immortalized cell lines, our de novo and uninterrupted primary culture labeling protocol (DUP‐SILAC) resulted in sufficient incorporation of SILAC labels for mass spectrometry‐based proteomic profiling. In addition, label incorporation did not alter their morphology and response to endotoxin stimulation. Proteomic analysis of the endotoxin‐stimulated SILAC‐labeled primary microglia identified expected as well as potentially novel activation markers and pro‐inflammatory pathways that could be quantified in a more physiologically relevant cellular model system compared to immortalized cell lines. The establishment of primary microglia SILAC model will further expand our capacity for global scale proteomic profiling of pathways under various physiological and pathological conditions. Proteomic MS data are available via ProteomeXchange with identifier PXD002759.     

The advantage of laser‐capture microdissection over whole tissue analysis in proteomic profiling studies

Laser‐capture microdissection (LCM) offers a reliable cell population enrichment tool and has been successfully coupled to MS analysis. Despite this, most proteomic studies employ whole tissue lysate (WTL) analysis in the discovery of disease biomarkers and in profiling analyses. Furthermore, the influence of tissue heterogeneity in WTL analysis, nor its impact in biomarker discovery studies have been completely elucidated. In order to address this, we compared previously obtained high resolution MS data from a cohort of 38 breast cancer tissues, of which both LCM enriched tumor epithelial cells and WTL samples were analyzed. Label‐free quantification (LFQ) analysis through MaxQuant software showed a significantly higher number of identified and quantified proteins in LCM enriched samples (3404) compared to WTLs (2837). Furthermore, WTL samples displayed a higher amount of missing data compared to LCM both at peptide and protein levels (p‐value < 0.001). 2D analysis on co‐expressed proteins revealed discrepant expression of immune system and lipid metabolisms related proteins between LCM and WTL samples. We hereby show that LCM better dissected the biology of breast tumor epithelial cells, possibly due to lower interference from surrounding tissues and highly abundant proteins. All data have been deposited in the ProteomeXchange with the dataset identifier PXD002381 ( http://proteomecentral.proteomexchange.org/dataset/PXD002381 ).     

Genetic and epigenetic analysis of non-small cell lung cancer with NotI-microarrays

This study aimed to clarify genetic and epigenetic alterations that occur during lung carcinogenesis and to design perspective sets of newly identified biomarkers. The original method includes chromosome 3 specific NotI-microarrays containing 180 NotI clones associated with genes for hybridization with 40 paired normal/tumor DNA samples of primary lung tumors: 28 squamous cell carcinomas (SCC) and 12 adenocarcinomas (ADC). The NotI-microarray data were confirmed by qPCR and bisulfite sequencing analyses. Forty-four genes showed methylation and/or deletions in more than 15% of non–small cell lung cancer (NSCLC) samples. In general, SCC samples were more frequently methylated/deleted than ADC. Moreover, the SCC alterations were observed already at stage I of tumor development, whereas in ADC many genes showed tumor progression specific methylation/deletions. Among genes frequently methylated/deleted in NSCLC, only a few were already known tumor suppressor genes: RBSP3 (CTDSPL), VHL and THRB. The RPL32, LOC285205, FGD5 and other genes were previously not shown to be involved in lung carcinogenesis. Ten methylated genes, i.e., IQSEC1, RBSP3, ITGA9, FOXP1, LRRN1, GNAI2, VHL, FGD5, ALDH1L1 and BCL6 were tested for expression by qPCR and were found downregulated in the majority of cases. Three genes (RBSP3, FBLN2 and ITGA9) demonstrated strong cell growth inhibition activity. A comprehensive statistical analysis suggested the set of 19 gene markers, ANKRD28, BHLHE40, CGGBP1, RBSP3, EPHB1, FGD5, FOXP1, GORASP1/TTC21, IQSEC1, ITGA9, LOC285375, LRRC3B, LRRN1, MITF, NKIRAS1/RPL15, TRH, UBE2E2, VHL, WNT7A, to allow early detection, tumor progression, metastases and to discriminate between SCC and ADC with sensitivity and specificity of 80–100%.     

Reference proteome of highly purified human Th1 cells reveals strong effects on metabolism and protein ubiquitination upon differentiation

The differentiation of human CD4⁺ T cells into T helper cell subtypes and regulatory T cells is crucial to the immune response. Among subtypes, Th1 cells are dominant, representing approximately 50% of all lymphocytes. Thus far, most global proteomic studies have used only partially purified T helper cell subpopulations and/or have employed artificial protocols for inducing specific T helper cell subtypes and/or used gel‐based approaches. These studies have shed light on molecular details of certain aspects of the proteome; nevertheless a global analysis of high purity primary naïve and Th1 cells by LC‐MS/MS is required to provide a reference dataset for proteome‐based T cell subtype characterization. The utilization of highly purified Th1 cells for a global proteome assessment and the bioinformatic comparison to naïve cells reveals changes in cell metabolism and the ubiquitination pathway upon T cell differentiation. All MS data have been deposited in the ProteomeXchange with identifier PXD001066 ( http://proteomecentral.proteomexchange.org/dataset/PXD001066 ).     

Proteomics Identification and Validation of Desmocollin‐1 and Catechol‐O‐Methyltransferase as Proteins Associated with Breast Cancer Cell Migration and Metastasis

Biological treatment of many cancers currently targets membrane bound receptors located on a cell surface. To identify novel membrane proteins associated with migration and metastasis of breast cancer cells, a more migrating subpopulation of MDA‐MB‐231 breast cancer cell line is selected and characterized. A high‐resolution quantitative mass spectrometry with SILAC labeling is applied to analyze their surfaceome and it is compared with that of parental MDA‐MB‐231 cells. Among 824 identified proteins (FDR < 0.01), 128 differentially abundant cell surface proteins with at least one transmembrane domain are found. Of these, i) desmocollin‐1 (DSC1) is validated as a protein connected with lymph node status of luminal A breast cancer, tumor grade, and Her‐2 status by immunohistochemistry in the set of 96 primary breast tumors, and ii) catechol‐O‐methyltransferase is successfully verified as a protein associated with lymph node metastasis of triple negative breast cancer as well as with tumor grade by targeted data extraction from the SWATH‐MS data of the same set of tissues. The findings indicate importance of both proteins for breast cancer development and metastasis and highlight the potential of biomarker validation strategy via targeted data extraction from SWATH‐MS datasets.     

Research on circadian clock genes in non-small-cell lung carcinoma

Circadian clock genes have become a hot topic in cancer research in recent years, and more and more studies are showing that clock genes are involved in regulating cell proliferation cycle and apoptosis of malignant tumors, neuroendocrine and immune function, and other processes. Lung cancer is a malignant tumor with increasing incidence worldwide. The pathogenesis of lung cancer is extremely complicated and includes genetic factors, living environment, and smoking, and the occurrence of lung cancer is related to the regulation of many oncogenes and tumor suppressor genes. But there are few studies on clock genes in lung cancer. Studies on clock genes may help to better understand the mechanism of lung cancer development for an improved treatment. The expressions of all 14 kinds of clock genes in adenocarcinoma (ADC) and squamous cell carcinoma (SCC), two main kinds of non-small-cell lung cancer (NSCLC), were studied based on integration and analysis of data from The Cancer Genome Atlas (TCGA) to show the association between clock gene expression and prognosis of cancer patients. Analysis of TCGA data indicated that overexpression of Cry2, BMAL1, and RORA with underexpression of Timeless and NPAS2 was associated with a favorable prognosis of ADC, and the expression of NPAS2 was associated with the time of patient survival. Additionally, the expression of Cry2 was related to TNM stage. In SCC, high expression of DEC1 was correlated with poor overall survival in patients and the expression of Timeless was associated with the time of patient survival. In NSCLC, circadian clock genes constitute cancer circadian rhythm by interacting with each other, showing that asynchrony with normal tissues, which collectively controlling the occurrence and development of NSCLC.