Proteomics and Disease Revisited: The Challenge of Providing Proteomic Tools into Clinical Practice

N-glycosylated GPNMB ligand independently activates mutated EGFR signaling and promotes metastasis in NSCLC

Lung cancer is the leading cause of cancer‐related death worldwide. As well as the identified role of epidermal growth factor receptor (EGFR), its association with driver mutations has improved the therapeutics for patients with lung cancer harboring EGFR mutations. These patients usually display shorter overall survival and a higher tendency to develop distant metastasis compared with those carrying the wild‐type EGFR. Nevertheless, the way to control mutated EGFR signaling remains unclear. Here, we performed membrane proteomic analysis to determine potential components that may act with EGFR mutations to promote lung cancer malignancy. Expression of transmembrane glycoprotein non‐metastatic melanoma protein B (GPNMB) was positively correlated with the status of mutated EGFR in non‐small‐cell lung cancer (NSCLC). This protein was not only overexpressed but also highly glycosylated in EGFR‐mutated, especially EGFR‐L858R mutated, NSCLC cells. Further examination showed that GPNMB could activate mutated EGFR without ligand stimulation and could bind to the C‐terminus of EGFR, assist phosphorylation at Y845, turn on downstream STAT3 signaling, and promote cancer metastasis. Moreover, we also found that Asn134 (N134) glycosylation of GPNMB played a crucial role in this ligand‐independent regulation. Depleting N134‐glycosylation on GPNMB could dramatically inhibit binding of GPNMB to mutated EGFR, blocking its downstream signaling, and ultimately inhibiting cancer metastasis in NSCLC. Clarifying the role of N‐glycosylated GPNMB in regulating the ligand‐independent activation of mutated EGFR may soon give new insight into the development of novel therapeutics for NSCLC.

Disease-related cellular protein networks differentially affected under different EGFR mutations in lung adenocarcinoma

It is unclear how epidermal growth factor receptor EGFR major driver mutations (L858R or Ex19del) affect downstream molecular networks and pathways. This study aimed to provide information on the influences of these mutations. The study assessed 36 protein expression profiles of lung adenocarcinoma (Ex19del, nine; L858R, nine; no Ex19del/L858R, 18). Weighted gene co-expression network analysis together with analysis of variance-based screening identified 13 co-expressed modules and their eigen proteins. Pathway enrichment analysis for the Ex19del mutation demonstrated involvement of SUMOylation, epithelial and mesenchymal transition, ERK/mitogen-activated protein kinase signalling via phosphorylation and Hippo signalling. Additionally, analysis for the L858R mutation identified various pathways related to cancer cell survival and death. With regard to the Ex19del mutation, ROCK, RPS6KA1, ARF1, IL2RA and several ErbB pathways were upregulated, whereas AURK and GSKIP were downregulated. With regard to the L858R mutation, RB1, TSC22D3 and DOCK1 were downregulated, whereas various networks, including VEGFA, were moderately upregulated. In all mutation types, CD80/CD86 (B7), MHC, CIITA and IFGN were activated, whereas CD37 and SAFB were inhibited. Costimulatory immune-checkpoint pathways by B7/CD28 were mainly activated, whereas those by PD-1/PD-L1 were inhibited. Our findings may help identify potential therapeutic targets and develop therapeutic strategies to improve patient outcomes.

Current status of clinical proteogenomics in lung cancer

Introduction: Lung cancer is the leading cause of cancer death worldwide. Proteogenomics, a way to integrate genomics, transcriptomics, and proteomics, have emerged as a way to understand molecular causes in cancer tumorigenesis. This understanding will help identify therapeutic targets that are urgently needed to improve individual patient outcomes. Areas covered: To explore underlying molecular mechanisms of lung cancer subtypes, several efforts have used proteogenomic approaches that integrate next generation sequencing (NGS) and mass spectrometry (MS)-based technologies. Expert opinion: A large-scale, MS-based, proteomic analysis, together with both NGS-based genomic data and clinicopathological information, will facilitate establishing extensive databases for lung cancer subtypes that can be used for further proteogenomic analyzes. Proteogenomic strategies will further be understanding of how major driver mutations affect downstream molecular networks, resulting in lung cancer progression and malignancy, and how therapy-resistant cancers resistant are molecularly structured. These strategies require advanced bioinformatics based on a dynamic theory of network systems, rather than statistics, to accurately identify mutant proteins and their affected key networks.

Identification of key modules and hub genes for small-cell lung carcinoma and large-cell neuroendocrine lung carcinoma by weighted gene co-expression network analysis of clinical tissue-proteomes

Small-cell lung carcinoma (SCLC) and large-cell neuroendocrine lung carcinoma (LCNEC) are high-grade lung neuroendocrine tumors (NET). However, comparative protein expression within SCLC and LCNEC remains unclear. Here, protein expression profiles were obtained via mass spectrometry-based proteomic analysis. Weighted gene co-expression network analysis (WGCNA) identified co-expressed modules and hub genes. Of 34 identified modules, six were significant and selected for protein-protein interaction (PPI) network analysis and pathway enrichment. Within the six modules, the activation of cellular processes and complexes, such as alternative mRNA splicing, translation initiation, nucleosome remodeling and deacetylase (NuRD) complex, SWItch/Sucrose Non-Fermentable (SWI/SNF) superfamily-type complex, chromatin remodeling pathway, and mRNA metabolic processes, were significant to SCLC. Modules enriched in processes, including signal recognition particle (SRP)-dependent co-translational protein targeting to membrane, nuclear-transcribed mRNA catabolic process of nonsense-mediated decay (NMD), and cellular macromolecule catabolic process, were characteristically activated in LCNEC. Novel high-degree hub genes were identified for each module. Master and upstream regulators were predicted via causal network analysis. This study provides an understanding of the molecular differences in tumorigenesis and malignancy between SCLC and LCNEC and may help identify potential therapeutic targets.

Recent mass spectrometry-based proteomics for biomarker discovery in lung cancer, COPD, and asthma

INTRODUCTION

Lung cancer and related diseases have been one of the most common causes of deaths worldwide. Genomic-based biomarkers may hardly reflect the underlying dynamic molecular mechanism of functional protein interactions, which is the center of a disease. Recent developments in mass spectrometry (MS) have made it possible to analyze disease-relevant proteins expressed in clinical specimens by proteomic challenges. Areas covered: To understand the molecular mechanisms of lung cancer and its subtypes, chronic obstructive pulmonary disease (COPD), asthma and others, great efforts have been taken to identify numerous relevant proteins by MS-based clinical proteomic approaches. Since lung cancer is a multifactorial disease that is biologically associated with asthma and COPD among various lung diseases, this study focused on proteomic studies on biomarker discovery using various clinical specimens for lung cancer, COPD, and asthma. Expert commentary: MS-based exploratory proteomics utilizing clinical specimens, which can incorporate both experimental and bioinformatic analysis of protein-protein interaction and also can adopt proteogenomic approaches, makes it possible to reveal molecular networks that are relevant to a disease subgroup and that could differentiate between drug responders and non-responders, good and poor prognoses, drug resistance, and so on.

Mass Spectrometry-Based Metabolomic and Proteomic Strategies in Organic Acidemias

Organic acidemias (OAs) are inherited metabolic disorders caused by deficiency of enzymatic activities in the catabolism of amino acids, carbohydrates, or lipids. These disorders result in the accumulation of mono-, di-, or tricarboxylic acids, generally referred to as organic acids. The OA outcomes can involve different organs and/or systems. Some OA disorders are easily managed if promptly diagnosed and treated, whereas, in others cases, such as propionate metabolism-related OAs (propionic acidemia, PA; methylmalonic acidemia, MMA), neither diet, vitamin therapy, nor liver transplantation appears to prevent multiorgan impairment. Here, we review the recent developments in dissecting molecular bases of OAs by using integration of mass spectrometry- (MS-) based metabolomic and proteomic strategies. MS-based techniques have facilitated the rapid and economical evaluation of a broad spectrum of metabolites in various body fluids, also collected in small samples, like dried blood spots. This approach has enabled the timely diagnosis of OAs, thereby facilitating early therapeutic intervention. Besides providing an overview of MS-based approaches most frequently used to study the molecular mechanisms underlying OA pathophysiology, we discuss the principal challenges of metabolomic and proteomic applications to OAs.

A proteomic profile of synoviocyte lesions microdissected from formalin-fixed paraffin-embedded synovial tissues of rheumatoid arthritis

Background

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic inflammation of the synovial joints. Early intervention followed by early diagnosis can result in disease remission; however, both early stage diagnosis and provision of effective treatment have been impeded by the heterogeneity of RA, which details of pathological mechanism are unclear. Regardless of numerous investigations of RA by means of genomic and proteomic approaches, proteins interplaying in RA synovial tissues that contain various types of synoviocytes, are not yet sufficiently understood. Hence we have conducted an HPLC/mass spectrometry-based exploratory proteomic analysis focusing on synoviocyte lesions laser-microdissected (LMD) from formalin-fixed paraffin-embedded (FFPE) synovial tissues (RA, n = 15; OA, n = 5), where those of Osteoarthritis (OA) were used as the control.

Results

A total of 508 proteins were identified from the RA and OA groups. With the semi-quantitative comparisons, the spectral index (SpI), log2 protein ratio (R_SC) based on spectral counting, and statistical G-test, 98 proteins were found to be significant (pair-wise p < 0.05) to the RA synovial tissues. These include stromelysin-1 (MMP3), proteins S100-A8 and S100-A9, plastin-2, galectin-3, calreticulin, cathepsin Z, HLA-A, HLA-DRB1, ferritin, neutrophil defensin 1, CD14, MMP9 etc.

Conclusions

Our results confirmed the involvement of known RA biomarkers such as stromelysin-1 (MMP3) and proteins S100-A8 and S100-A9, and also that of leukocyte antigens such as HLA-DRB1. Network analyses of protein–protein interaction for those proteins significant to RA revealed a dominant participation of ribosome pathway (p = 5.91 × 10⁻⁴⁵), and, interestingly, the associations of the p53 signaling (p = 2.34 × 10⁻⁵). An involvement of proteins including CD14, S100-A8/S100-A9 seems to suggest an activation of the NF-kB/MAPK signaling pathway. Our strategy of laser-microdissected FFPE-tissue proteomic analysis in Rheumatoid Arthritis thus demonstrated its technical feasibility in profiling proteins expressed in synovial tissues, which may play important roles in the RA pathogenesis.

Electronic supplementary material

The online version of this article (doi:10.1186/s12014-015-9091-8) contains supplementary material, which is available to authorized users.

A proteomic profiling of laser-microdissected lung adenocarcinoma cells of early lepidic-types

Background

In the new pathologic classification of lung adenocarcinoma proposed by IASLC/ATS/ERS in 2011, lepidic type adenocarcinomas are constituted by three subtypes; adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and lepidic predominant invasive adenocarcinoma (LPIA). Although these subtypes are speculated to show sequential progression from preinvasive lesion to invasive lung cancer, changes of protein expressions during these processes have not been fully studied yet. This study aims to glimpse a proteomic view of the early lepidic type lung adenocarcinomas.

Methods

A total of nine formalin-fixed and paraffin-embedded (FFPE) lepidic type lung adenocarcinoma tissues were selected from our archives, three tissues each in AIS, MIA and LPIA. The tumor and peripheral non-tumor cells in these FFPE tissues were collected with laser microdissection (LMD). Using liquid chromatography-tandem mass spectrometry (MS/MS), protein compositions were compared with respect to the peptide separation profiles among tumors collected from three types of tissues, AIS, MIA and LPIA. Proteins identified were semi-quantified by spectral counting-based or identification-based approach, and statistical evaluation was performed by pairwise G-tests.

Results

A total of 840 proteins were identified. Spectral counting-based semi-quantitative comparisons of all identified proteins through AIS to LPIA have revealed that the protein expression profile of LPIA was significantly differentiated from other subtypes. 70 proteins including HPX, CTTN, CDH1, EGFR, MUC1 were found as LPIA-type marker candidates, 15 protein candidates for MIA-type marker included CRABP2, LMO7, and RNPEP, and 26 protein candidates for AIS-type marker included LTA4H and SOD2. The STRING gene set enrichment resulted from the protein-protein interaction (PPI) network analysis suggested that AIS was rather associated with pathways of focal adhesion, adherens junction, tight junction, that MIA had a strong association predominantly with pathways of proteoglycans in cancer and with PI3K-Akt. In contrast, LPIA was associated broadly with numerous tumor-progression pathways including ErbB, Ras, Rap1 and HIF-1 signalings.

Conclusions

The proteomic profiles obtained in this study demonstrated the technical feasibility to elucidate protein candidates differentially expressed in FFPE tissues of LPIA. Our results may provide candidates of disease-oriented proteins which may be related to mechanisms of the early-stage progression of lung adenocarcinoma.

Electronic supplementary material

The online version of this article (doi:10.1186/s40169-015-0064-3) contains supplementary material, which is available to authorized users.

State-of-the-art MS technology applications in lung disease

Two frontline MS technologies, which have recently gained much attention, are discussed within the scope of this review. Besides a brief summary on the contemporary state of lung cancer and chronic obstructive pulmonary disease, the principles of multiple reaction monitoring and matrix assisted laser desorption ionization (MALDI) MS imaging are presented. A comprehensive overview of quantitative mass spectrometry applications is provided, covering multiple reaction monitoring assay developments for analysis of proteins (biomarkers) and low-molecular-weight compounds (drugs) with a special focus on the disease areas of lung cancer and chronic obstructive pulmonary disease. The MALDI-MS imaging applications are discussed similarly, providing references to studies conducted on lung tissues in order to localize drug compounds and protein biomarkers.

Preferential expression of potential markers for cancer stem cells in large cell neuroendocrine carcinoma of the lung. An FFPE proteomic study

BACKGROUND

Large cell neuroendocrine carcinoma (LCNEC) of the lung, a subtype of large cell carcinoma (LCC), is characterized by neuroendocrine differentiation that small cell lung carcinoma (SCLC) shares. Pre-therapeutic histological distinction between LCNEC and SCLC has so far been problematic, leading to adverse clinical outcome. We started a project establishing protein targets characteristic of LCNEC with a proteomic method using formalin fixed paraffin-embedded (FFPE) tissues, which will help make diagnosis convincing.

METHODS

Cancer cells were collected by laser microdissection from cancer foci in FFPE tissues of LCNEC (n = 4), SCLC (n = 5), and LCC (n = 5) with definite histological diagnosis. Proteins were extracted from the harvested sections, trypsin-digested, and subjected to HPLC/mass spectrometry. Proteins identified by database search were semi-quantified by spectral counting and statistically sorted by pair-wise G-statistics. The results were immunohistochemically verified using a total of 10 cases for each group to confirm proteomic results.

RESULTS

A total of 1981 proteins identified from the three cancer groups were subjected to pair-wise G-test under p < 0.05 and specificity of a protein's expression to LCNEC was checked using a 3D plot with the coordinates comprising G-statistic values for every two group comparisons. We identified four protein candidates preferentially expressed in LCNEC compared with SCLC with convincingly low p-values: aldehyde dehydrogenase 1 family member A1 (AL1A1) (p = 6.1 × 10-4), aldo-keto reductase family 1 members C1 (AK1C1) (p = 9.6x10-10) and C3 (AK1C3) (p = 3.9x10-10) and CD44 antigen (p = 0.021). These p-values were confirmed by non-parametric exact inference tests. Interestingly, all these candidates would belong to cancer stem cell markers. Immunohistochmistry supported proteomic results.

CONCLUSIONS

These results suggest that candidate biomarkers of LCNEC were related to cancer stem cells and this proteomic approach via FFPE samples was effective to detect them.

Proteomics beyond proteomics: toward clinical applications

PURPOSE OF REVIEW

There is an increasing interest in the application of proteomics in all areas of the life sciences, especially in the area of biomedical research wherein the analysis of biological fluids is very promising for biomarker discovery. The rapid development of proteomics as a field has depended upon substantial advances in instrumentation, methodologies, software and the availability of comprehensive sequence databases. However, progress has been slower than anticipated with respect to application in the realm of biomedicine.

RECENT FINDINGS

We review some of the areas of importance for the development of proteomics and its applications to biomedical research.

SUMMARY

One of the factors explaining the slow progress of candidate proteomics biomarkers through the translational pipeline has been the difficulty to develop validation and standardization of procedures to improve reproducibility, sensitivity and specificity. This challenge has now largely been met by large, consortium efforts, leading to the discovery of drug-specific protein biomarkers. The need for integrating complex protein patterns is now recognized in a new test classification by the US Food and Drug Administration termed 'in-vitro diagnostic multivariate index assays'. Further progress in clinical proteomics will depend upon continued collaborative efforts and infrastructure development by the proteomics community.

Clinical proteomics: current status, challenges, and future perspectives

This account will give an overview and evaluation of the current advances in mass spectrometry (MS)-based proteomics platforms and technology. A general review of some background information concerning the application of these methods in the characterization of molecular sizes and related protein expression profiles associated with different types of cells under varied experimental conditions will be presented. It is intended to provide a concise and succinct overview to those clinical researchers first exposed to this foremost powerful methodology in modern life sciences of postgenomic era. Proteomic characterization using highly sophisticated and expensive instrumentation of MS has been used to characterize biological samples of complex protein mixtures with vastly different protein structure and composition. These systems are then used to highlight the versatility and potential of the MS-based proteomic strategies for facilitating protein expression analysis of various disease-related organisms or tissues of interest. Major MS-based strategies reviewed herein include (1) matrix-assisted laser desorption ionization-MS and electron-spray ionization proteomics; (2) one-dimensional or two-dimensional gel-based proteomics; (3) gel-free shotgun proteomics in conjunction with liquid chromatography/tandem MS; (4) Multiple reaction monitoring coupled tandem MS quantitative proteomics and; (5) Phosphoproteomics based on immobilized metal affinity chromatography and liquid chromatography-MS/MS.