Proteomic analysis of human saliva from lung cancer patients using two-dimensional difference gel electrophoresis and mass spectrometry

Lung cancer is often asymptomatic or causes only nonspecific symptoms in its early stages. Early detection represents one of the most promising approaches to reduce the growing lung cancer burden. Human saliva is an attractive diagnostic fluid because its collection is less invasive than that of tissue or blood. Profiling of proteins in saliva over the course of disease progression could reveal potential biomarkers indicative of oral or systematic diseases, which may be used extensively in future medical diagnostics. There were 72 subjects enrolled in this study for saliva sample collection according to the approved protocol. Two-dimensional difference gel electrophoresis combined with MS was the platform for salivary proteome separation, quantification, and identification from two pooled samples. Candidate proteomic biomarkers were verified and prevalidated by using immunoassay methods. There were 16 candidate protein biomarkers discovered by two-dimensional difference gel electrophoresis and MS. Three proteins were further verified in the discovery sample set, prevalidation sample set, and lung cancer cell lines. The discriminatory power of these candidate biomarkers in lung cancer patients and healthy control subjects can reach 88.5% sensitivity and 92.3% specificity with AUC = 0.90. This preliminary data report demonstrates that proteomic biomarkers are present in human saliva when people develop lung cancer. The discriminatory power of these candidate biomarkers indicate that a simple saliva test might be established for lung cancer clinical screening and detection.     

Mass spectrometric identification of human prostate cancer-derived proteins in serum of xenograft-bearing mice

Lack of sensitivity and specificity of current tumor markers has intensified research efforts to find new biomarkers. The identification of potential tumor markers in human body fluids is hampered by large variability and complexity of both control and patient samples, laborious biochemical analyses, and the fact that the identified proteins are unlikely produced by the diseased cells but are due to secondary body defense mechanisms. In a new approach presented here, we eliminate these problems by performing proteomic analysis in a prostate cancer xenograft model in which human prostate cancer cells form a tumor in an immune-incompetent nude mouse. Using this concept, proteins present in mouse serum that can be identified as human will, by definition, originate from the human prostate cancer xenograft and might have potential diagnostic and prognostic value. Using one-dimensional gel electrophoresis, liquid chromatography, and mass spectrometry, we identified tumor-derived human nm23/nucleoside-diphosphate kinase (NME) in the serum of a nude mouse bearing the androgen-independent human prostate cancer xenograft PC339. NME is known to be involved in the metastatic potential of several tumor cells, including prostate cancer cells. Furthermore we identified six human enzymes involved in glycolysis (fructose-bisphosphate aldolase A, triose-phosphate isomerase, glyceraldehyde-3-phosphate dehydrogenase, alpha enolase, and lactate dehydrogenases A and B) in the serum of the tumor-bearing mice. The presence of human NME and glyceraldehyde-3-phosphate dehydrogenase in the serum of PC339-bearing mice was confirmed by Western blotting. Although the putative usefulness of these proteins in predicting prognosis of prostate cancer remains to be determined, the present data illustrate that our approach is a promising tool for the focused discovery of new prostate cancer biomarkers.     

Integrated Proteomic Analysis of Human Cancer Cells and Plasma from Tumor Bearing Mice for Ovarian Cancer Biomarker Discovery

Background

The complexity of the human plasma proteome represents a substantial challenge for biomarker discovery. Proteomic analysis of genetically engineered mouse models of cancer and isolated cancer cells and cell lines provide alternative methods for identification of potential cancer markers that would be detectable in human blood using sensitive assays. The goal of this work is to evaluate the utility of an integrative strategy using these two approaches for biomarker discovery.

Methodology/Principal Findings

We investigated a strategy that combined quantitative plasma proteomics of an ovarian cancer mouse model with analysis of proteins secreted or shed by human ovarian cancer cells. Of 106 plasma proteins identified with increased levels in tumor bearing mice, 58 were also secreted or shed from ovarian cancer cells. The remainder consisted primarily of host-response proteins. Of 25 proteins identified in the study that were assayed, 8 mostly secreted proteins common to mouse plasma and human cancer cells were significantly upregulated in a set of plasmas from ovarian cancer patients. Five of the eight proteins were confirmed to be upregulated in a second independent set of ovarian cancer plasmas, including in early stage disease.

Conclusions/Significance

Integrated proteomic analysis of cancer mouse models and human cancer cell populations provides an effective approach to identify potential circulating protein biomarkers.     

Comparisons of microRNA Patterns in Plasma before and after Tumor Removal Reveal New Biomarkers of Lung Squamous Cell Carcinoma

Lung cancer is the major human malignancy, accounting for 30% of all cancer-related deaths worldwide. Poor survival of lung cancer patients, together with late diagnosis and resistance to classic chemotherapy, highlights the need for identification of new biomarkers for early detection. Among different cancer biomarkers, small non-coding RNAs called microRNAs (miRNAs) are considered the most promising, owing to their remarkable stability, their cancer-type specificity, and their presence in body fluids. However, results of multiple previous attempts to identify circulating miRNAs specific for lung cancer are inconsistent, likely due to two main reasons: prominent variability in blood miRNA content among individuals and difficulties in distinguishing tumor-relevant miRNAs in the blood from their non-tumor counterparts. To overcome these impediments, we compared circulating miRNA profiles in patients with lung squamous cell carcinoma (SCC) before and after tumor removal, assuming that the levels of all tumor-relevant miRNAs would drop after the surgery. Our results revealed a specific panel of the miRNAs (miR-205, -19a, -19b, -30b, and -20a) whose levels decreased strikingly in the blood of patients after lung SCC surgery. Interestingly, miRNA profiling of plasma fractions of lung SCC patients revealed high levels of these miRNA species in tumor-specific exosomes; additionally, some of these miRNAs were also found to be selectively secreted to the medium by cultivated lung cancer cells. These results strengthen the notion that tumor cells secrete miRNA-containing exosomes into circulation, and that miRNA profiling of the exosomal plasma fraction may reveal powerful cancer biomarkers.     

A novel 3D heterotypic spheroid model for studying extracellular vesicle-mediated tumour and immune cell communication

Cancer-derived extracellular vesicles (EVs) have emerged as important mediators of tumour-host interactions, and they have been shown to exert various functional effects in immune cells. In most of the studies on human immune cells, EVs have been isolated from cancer cell culture medium or patients' body fluids and added to the immune cell cultures. In such a setting, the physiological relevance of the chosen EV concentration is unknown and the EV isolation method and the timing of EV administration may bias the results. In the current study we aimed to develop an experimental cell culture model to study EV-mediated effects in human T and B cells at conditions mimicking the tumour microenvironment. We constructed a human prostate cancer cell line PC3 producing GFP-tagged EVs (PC3-CD63-GFP cells) and developed a 3D heterotypic spheroid model composed of PC3-CD63-GFP cells and human peripheral blood mononuclear cells (PBMCs). The transfer of GFP-tagged EVs from PC3-CD63-GFP cells to the lymphocytes was analysed by flow cytometry and fluorescence imaging. The endocytic pathway was investigated using three endocytosis inhibitors. Our results showed that GFP-tagged EVs interacted with a large fraction of B cells, however, the majority of EVs were not internalised by B cells but rather remained bound at the cell surface. T cell subsets differed in their ability to interact with the EVs - 15.7–24.1% of the total CD3⁺ T cell population interacted with GFP-tagged EVs, while only 0.3–5.8% of CD8⁺ T were GFP positive. Furthermore, a fraction of EVs were internalised in CD3⁺ T cells via macropinocytosis. Taken together, the heterotypic PC3-CD63-GFP and PBMC spheroid model provides the opportunity to study the interactions and functional effects of cancer-derived EVs in human immune cells at conditions mimicking the tumour microenvironment.     

Methylated DNA/RNA in Body Fluids as Biomarkers for Lung Cancer

DNA/RNA methylation plays an important role in lung cancer initiation and progression. Liquid biopsy makes use of cells, nucleotides and proteins released from tumor cells into body fluids to help with cancer diagnosis and prognosis. Methylation of circulating tumor DNA (ctDNA) has gained increasing attention as biomarkers for lung cancer. Here we briefly introduce the biological basis and detection method of ctDNA methylation, and review various applications of methylated DNA in body fluids in lung cancer screening, diagnosis, prognosis, monitoring and treatment prediction. We also discuss the emerging role of RNA methylation as biomarkers for cancer.     

A mouse model repository for cancer biomarker discovery

Early detection of cancer using biomarkers obtained from blood or other easily accessible tissues would have a significant impact on reducing cancer mortality. However, identifying new blood-based biomarkers has been hindered by the dynamic complexity of the human plasma proteome, confounded by genetic and environmental variability, and the scarcity of high quality controlled samples. In this report, we discuss a new paradigm for biomarker discovery through the use of mouse models. Inbred mouse models of cancer recapitulate many critical features of human cancer, while eliminating sources of environmental and genetic variability. The ability to collect samples from highly matched cases and controls under identical conditions further reduces variability which is critical for successful biomarker discovery. We describe the establishment of a repository containing tumor, plasma, urine, and other tissues from 10 different mouse models of human cancer, including two breast, two lung, two prostate, two gastrointestinal, one ovarian, and one skin tumor model. We present the overall design of this resource and its potential use by the research community for biomarker discovery.     

Exosomes: Generation,structure, transport,biological activity,and diagnostic application

Cells of almost all tissues secrete to the extracellular environment a variety of vesicular structures. The most interesting vesicles are exosomes–microvesicles ranging from 30 to 100 nm in size. These vesicles contain various RNA, including mRNA, microRNA, as well as membrane and cytoplasmic proteins that can be transported in these particles to nearby and distantly located cells of various tissues using physiological fluids (blood, urine, saliva, etc.). Exosomes are necessary for normal functioning of the organism and their repertoire changes during the development of pathologies. This review presents the data on generation, secretion, and transport of exosomes, their structure and roles in normal conditions and in the process of the malignant tumor development. Prospects of the application of exosomal biomarkers for the development of early non-invasive cancer diagnosis are also discussed.     

Biomarkers of Residual Disease,Disseminated Tumor Cells,and Metastases in the MMTV-PyMT Breast Cancer Model

Cancer metastases arise in part from disseminated tumor cells originating from the primary tumor and from residual disease persisting after therapy. The identification of biomarkers on micro-metastases, disseminated tumors, and residual disease may yield novel tools for early detection and treatment of these disease states prior to their development into metastases and recurrent tumors. Here we describe the molecular profiling of disseminated tumor cells in lungs, lung metastases, and residual tumor cells in the MMTV-PyMT breast cancer model. MMTV-PyMT mice were bred with actin-GFP mice, and focal hyperplastic lesions from pubertal MMTV-PyMT;actin-GFP mice were orthotopically transplanted into FVB/n mice to track single tumor foci. Tumor-bearing mice were treated with TAC chemotherapy (docetaxel, doxorubicin, cyclophosphamide), and residual and relapsed tumor cells were sorted and profiled by mRNA microarray analysis. Data analysis revealed enrichment of the Jak/Stat pathway, Notch pathway, and epigenetic regulators in residual tumors. Stat1 was significantly up-regulated in a DNA-damage-resistant population of residual tumor cells, and a pre-existing Stat1 sub-population was identified in untreated tumors. Tumor cells from adenomas, carcinomas, lung disseminated tumor cells, and lung metastases were also sorted from MMTV-PyMT transplant mice and profiled by mRNA microarray. Whereas disseminated tumors cells appeared similar to carcinoma cells at the mRNA level, lung metastases were genotypically very different from disseminated cells and primary tumors. Lung metastases were enriched for a number of chromatin-modifying genes and stem cell-associated genes. Histone analysis of H3K4 and H3K9 suggested that lung metastases had been reprogrammed during malignant progression. These data identify novel biomarkers of residual tumor cells and disseminated tumor cells and implicate pathways that may mediate metastasis formation and tumor relapse after therapy.     

Urinary Volatile Compounds as Biomarkers for Lung Cancer: A Proof of Principle Study Using Odor Signatures in Mouse Models of Lung Cancer

A potential strategy for diagnosing lung cancer, the leading cause of cancer-related death, is to identify metabolic signatures (biomarkers) of the disease. Although data supports the hypothesis that volatile compounds can be detected in the breath of lung cancer patients by the sense of smell or through bioanalytical techniques, analysis of breath samples is cumbersome and technically challenging, thus limiting its applicability. The hypothesis explored here is that variations in small molecular weight volatile organic compounds (“odorants”) in urine could be used as biomarkers for lung cancer. To demonstrate the presence and chemical structures of volatile biomarkers, we studied mouse olfactory-guided behavior and metabolomics of volatile constituents of urine. Sensor mice could be trained to discriminate between odors of mice with and without experimental tumors demonstrating that volatile odorants are sufficient to identify tumor-bearing mice. Consistent with this result, chemical analyses of urinary volatiles demonstrated that the amounts of several compounds were dramatically different between tumor and control mice. Using principal component analysis and supervised machine-learning, we accurately discriminated between tumor and control groups, a result that was cross validated with novel test groups. Although there were shared differences between experimental and control animals in the two tumor models, we also found chemical differences between these models, demonstrating tumor-based specificity. The success of these studies provides a novel proof-of-principle demonstration of lung tumor diagnosis through urinary volatile odorants. This work should provide an impetus for similar searches for volatile diagnostic biomarkers in the urine of human lung cancer patients.     

Serum proteomics of lung adenocarcinomas induced by targeted overexpression of c-raf in alveolar epithelium identifies candidate biomarkers

We previously reported a proteome map of lung adenocarcinomas in serine-threonine kinase of the Raf family (c-raf) transgenic mice. We now extend our initial studies to serum proteins at early stage (1 month) and advanced stages of tumorigenesis (12 months). Notably, serum proteins from wild-type and tumor bearing mice were extracted with a lysis buffer containing 5 mol/L urea, 2 mol/L thiourea, 40 mmol/L Tris, 4% CHAPS, 100 mmol/L DTT, 0.5% BioLyte 3-10, separated by 2-DE and studied by image analysis. On average 400 protein spots per gel were excised and analyzed by MALDI-TOF MS. We identified 45 common and 5 uniquely expressed proteins in wild-type and tumor bearing mice. Apart from uniquely identified proteins we observed for n = 9 proteins differential expression when wild-type and tumor bearing mice were compared. This included serpins and other protease inhibitors, lipocalins, transthyretins, globins, and Igs. Notably, we demonstrate significant regulation of alpha-1-antitrypsin, alpha-2-macroglobulin, hemoglobin subunit alpha, vitamin D-binding protein, major urinary proteins, and transthyretin (up to eight-fold) in serum of lung tumor bearing mice. Disease association of these proteins in human malignancies has been reported. Thus, an identification of regulated serum proteins in this lung cancer disease model provides excellent opportunities for the search of novel biomarkers.     

The cancer secretome,current status and opportunities in the lung,breast and colorectal cancer context

Despite major improvements on the knowledge and clinical management, cancer is still a deadly disease. Novel biomarkers for better cancer detection, diagnosis and treatment prediction are urgently needed. Proteins secreted, shed or leaking from the cancer cell, collectively termed the cancer secretome, are promising biomarkers since they might be detectable in blood or other biofluids. Furthermore, the cancer secretome in part represents the tumor microenvironment that plays a key role in tumor promoting processes such as angiogenesis and invasion. The cancer secretome, sampled as conditioned medium from cell lines, tumor/tissue interstitial fluid or tumor proximal body fluids, can be studied comprehensively by nanoLC-MS/MS-based approaches. Here, we outline the importance of current cancer secretome research and describe the mass spectrometry-based analysis of the secretome. Further, we provide an overview of cancer secretome research with a focus on the three most common cancer types: lung, breast and colorectal cancer. We conclude that the cancer secretome research field is a young, but rapidly evolving research field. Up to now, the focus has mainly been on the discovery of novel promising secreted cancer biomarker proteins. An interesting finding that merits attention is that in cancer unconventional secretion, e.g. via vesicles, seems increased. Refinement of current approaches and methods and progress in clinical validation of the current findings are vital in order to move towards applications in cancer management. This article is part of a Special Issue entitled: An Updated Secretome.     

Biomarkers for the lung cancer diagnosis and their advances in proteomics

Over a last decade, intense interest has been focused on biomarker discovery and their clinical uses. This interest is accelerated by the completion of human genome project and the progress of techniques in proteomics. Especially, cancer biomarker discovery is eminent in this field due to its anticipated critical role in early diagnosis, therapy guidance, and prognosis monitoring of cancers. Among cancers, lung cancer, one of the top three major cancers, is the one showing the highest mortality because of failure in early diagnosis. Numerous potential DNA biomarkers such as hypermethylations of the promoters and mutations in K-ras, p53, and protein biomarkers; carcinoembryonic antigen (CEA), CYFRA21-1, plasma kallikrein B1 (KLKB1), Neuron-specific enolase, etc. have been discovered as lung cancer biomarkers. Despite extensive studies thus far, few are turned out to be useful in clinic. Even those used in clinic do not show enough sensitivity, specificity and reproducibility for general use. This review describes what the cancer biomarkers are for, various types of lung cancer biomarkers discovered at present and predicted future advance in lung cancer biomarker discovery with proteomics technology.     

Extracellular heat shock proteins and cancer: New perspectives

Heat shock proteins (HSPs) are a large family of molecular chaperones aberrantly expressed in cancer. The expression of HSPs in tumor cells has been shown to be implicated in the regulation of apoptosis, immune responses, angiogenesis and metastasis. Given that extracellular vesicles (EVs) can serve as potential source for the discovery of clinically useful biomarkers and therapeutic targets, it is of particular interest to study proteomic profiling of HSPs in EVs derived from various biological fluids of cancer patients. Furthermore, a divergent expression of circulating microRNAs (miRNAs) in patient samples has opened new opportunities in exploiting miRNAs as diagnostic tools. Herein, we address the current literature on the expression of extracellular HSPs with particular interest in HSPs in EVs derived from various biological fluids of cancer patients and different types of immune cells as promising targets for identification of clinical biomarkers of cancer. We also discuss the emerging role of miRNAs in HSP regulation for the discovery of blood-based biomarkers of cancer. We outline the importance of understanding relationships between various HSP networks and co-chaperones and propose the model for identification of HSP signatures in cancer. Elucidating the role of HSPs in EVs from the proteomic and miRNAs perspectives may provide new opportunities for the discovery of novel biomarkers of cancer.     

Proteome profiling for the identification of lung cancer signatures

Evaluation of: Taguchi A, Politi K, Pitteri SJ et al. Lung cancer signatures in plasma based on proteome profiling of mouse tumor models. Cancer Cell 20(3), 289–299 (2011).

Comprehensive and in-depth discovery of the disease proteome is an important issue in recent proteomics developments. Previous studies have shown a number of biomarkers discovered in various diseases, including lung cancer. Some of them are potentially useful in lung cancer diagnostics and prognostics. However, few of them can act as organ-specific biomarkers to extensively compare multiple cancer models. This article evaluates a recently published study employing comparative proteomics on multiple genetically engineered mouse models and sheds light on the usefulness and application of the discovered marker panel for human lung cancer diagnostics.