Lung cancer signatures in plasma based on proteome profiling of mouse tumor models

Quantitative Secretomic Analysis Identifies Extracellular Protein Factors That Modulate the Metastatic Phenotype of Non-Small Cell Lung Cancer

Lung cancer is the leading cause of cancer-related deaths for men and women in the United States, with non-small cell lung cancer (NSCLC) representing 85% of all diagnoses. Late stage detection, metastatic disease and lack of actionable biomarkers contribute to the high mortality rate. Proteins in the extracellular space are known to be critically involved in regulating every stage of the pathogenesis of lung cancer. To investigate the mechanism by which secreted proteins contribute to the pathogenesis of NSCLC, we performed quantitative secretomic analysis of two isogenic NSCLC cell lines (NCI-H1993 and NCI-H2073) and an immortalized human bronchial epithelial cell line (HBEC3-KT) as control. H1993 was derived from a chemo-naïve metastatic tumor, while H2073 was derived from the primary tumor after etoposide/cisplatin therapy. From the conditioned media of these three cell lines, we identified and quantified 2713 proteins, including a series of proteins involved in regulating inflammatory response, programmed cell death and cell motion. Gene Ontology (GO) analysis indicates that a number of proteins overexpressed in H1993 media are involved in biological processes related to cancer metastasis, including cell motion, cell-cell adhesion and cell migration. RNA interference (RNAi)-mediated knock down of a number of these proteins, including SULT2B1, CEACAM5, SPRR3, AGR2, S100P, and S100A14, leads to dramatically reduced migration of these cells. In addition, meta-analysis of survival data indicates NSCLC patients whose tumors express higher levels of several of these secreted proteins, including SULT2B1, CEACAM5, SPRR3, S100P, and S100A14, have a worse prognosis. Collectively, our results provide a potential molecular link between deregulated secretome and NSCLC cell migration/metastasis. In addition, the identification of these aberrantly secreted proteins might facilitate the development of biomarkers for early detection of this devastating disease.

Alzheimer's as a Systems-Level Disease Involving the Interplay of Multiple Cellular Networks

Alzheimer's disease (AD), and many neurodegenerative disorders, are multifactorial in nature. They involve a combination of genomic, epigenomic, interactomic and environmental factors. Progress is being made, and these complex diseases are beginning to be understood as having their origin in altered states of biological networks at the cellular level. In the case of AD, genomic susceptibility and mechanisms leading to (or accompanying) the impairment of the central Amyloid Precursor Protein (APP) processing and tau networks are widely accepted as major contributors to the diseased state. The derangement of these networks may result in both the gain and loss of functions, increased generation of toxic species (e.g., toxic soluble oligomers and aggregates) and imbalances, whose effects can propagate to supra-cellular levels. Although well sustained by empirical data and widely accepted, this global perspective often overlooks the essential roles played by the main counteracting homeostatic networks (e.g., protein quality control/proteostasis, unfolded protein response, protein folding chaperone networks, disaggregases, ER-associated degradation/ubiquitin proteasome system, endolysosomal network, autophagy, and other stress-protective and clearance networks), whose relevance to AD is just beginning to be fully realized. In this chapter, an integrative perspective is presented. Alzheimer's disease is characterized to be a result of: (a) intrinsic genomic/epigenomic susceptibility and, (b) a continued dynamic interplay between the deranged networks and the central homeostatic networks of nerve cells. This interplay of networks will underlie both the onset and rate of progression of the disease in each individual. Integrative Systems Biology approaches are required to effect its elucidation. Comprehensive Systems Biology experiments at different 'omics levels in simple model organisms, engineered to recapitulate the basic features of AD may illuminate the onset and sequence of events underlying AD. Indeed, studies of models of AD in simple organisms, differentiated cells in culture and rodents are beginning to offer hope that the onset and progression of AD, if detected at an early stage, may be stopped, delayed, or even reversed, by activating or modulating networks involved in proteostasis and the clearance of toxic species. In practice, the incorporation of next-generation neuroimaging, high-throughput and computational approaches are opening the way towards early diagnosis well before irreversible cell death. Thus, the presence or co-occurrence of: (a) accumulation of toxic Aβ oligomers and tau species; (b) altered splicing and transcriptome patterns; (c) impaired redox, proteostatic, and metabolic networks together with, (d) compromised homeostatic capacities may constitute relevant 'AD hallmarks at the cellular level' towards reliable and early diagnosis. From here, preventive lifestyle changes and tailored therapies may be investigated, such as combined strategies aimed at both lowering the production of toxic species and potentiating homeostatic responses, in order to prevent or delay the onset, and arrest, alleviate, or even reverse the progression of the disease.

From Mice to Men and Back: An Assessment of Preclinical Model Systems for the Study of Lung Cancers

INTRODUCTION

Studies of preclinical models are essential for determining the biology of lung cancers and testing new and novel therapeutic approaches. We review the commonly used preclinical models for lung cancers and evaluate their strengths and weaknesses.

METHODS

We searched the MEDLINE database via PubMed using combinations of the following medical subject headings: lung cancer; animal models, mice; cell line, tumor; cell culture, mice; transgenic, mice; SCID, transplantation; heterologous; and genetic engineering. We reviewed the relevant published articles.

RESULTS

Multiple examples of the three major preclinical models-tumor cell lines, patient-derived xenografts, and genetically engineered mouse models-exist and have been used by investigators worldwide, with more than 15,000 relevant publications. Each model has its strengths and actual or potential weaknesses. In addition, newer forms of these models have been proposed or are in use as potential improvements over the conventional models.

CONCLUSIONS

A large number and variety of models have been developed and extensively used for the study of all major types of lung cancer. While they remain the cornerstone of preclinical studies, each model has its individual strengths and weaknesses. These must be carefully evaluated and applied to the proposed studies to obtain the maximum usefulness from the models.

Pancreatic preneoplastic lesions plasma signatures and biomarkers based on proteome profiling of mouse models

Background:

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies with a mortality that is almost identical to incidence. Because early detected PDAC is potentially curable, blood-based biomarkers that could detect currently developing neoplasia would improve patient survival and management. PDAC develops from pancreatic intraepithelial neoplasia (PanIN) lesions, graded from low grade (PanIN1) to high grade (PanIN3). We made the hypothesis that specific proteomic signatures from each precancerous stage exist and are detectable in plasma.

Methods:

We explored the peptide profiles of microdissected PanIN cells and of plasma samples corresponding to the different PanIN grade from genetically engineered mouse models of PDAC using capillary electrophoresis coupled to mass spectrometry (CE-MS) and Chip-MS/MS.

Results:

We successfully characterised differential peptides profiles from PanIN microdissected cells. We found that plasma from tumor-bearing mice and age-matched controls exhibit discriminative peptide signatures. We also determined plasma peptide signatures corresponding to low- and high-grade precancerous step present in the mice pancreas using the two mass spectrometry technologies. Importantly, we identified biomarkers specific of PanIN3.

Conclusions:

We demonstrate that benign and advanced PanIN lesions display distinct plasma peptide patterns. This strongly supports the perspectives of developing a non-invasive screening test for prediction and early detection of PDAC.

MAPRE1 as a plasma biomarker for early-stage colorectal cancer and adenomas

Blood-based biomarkers for early detection of colorectal cancer could complement current approaches to colorectal cancer screening. We previously identified the APC-binding protein MAPRE1 as a potential colorectal cancer biomarker. Here, we undertook a case-control validation study to determine the performance of MAPRE1 in detecting early colorectal cancer and colon adenoma and to assess the potential relevance of additional biomarker candidates. We analyzed plasma samples from 60 patients with adenomas, 30 with early colorectal cancer, 30 with advanced colorectal cancer, and 60 healthy controls. MAPRE1 and a set of 21 proteins with potential biomarker utility were assayed using high-density antibody arrays, and carcinoembryonic antigen (CEA) was assayed using ELISA. The biologic significance of the candidate biomarkers was also assessed in colorectal cancer mouse models. Plasma MAPRE1 levels were significantly elevated in both patients with adenomas and patients with colorectal cancer compared with controls (P < 0.0001). MAPRE1 and CEA together yielded an area under the curve of 0.793 and a sensitivity of 0.400 at 95% specificity for differentiating early colorectal cancer from controls. Three other biomarkers (AK1, CLIC1, and SOD1) were significantly increased in both adenoma and early colorectal cancer patient plasma samples and in plasma from colorectal cancer mouse models at preclinical stages compared with controls. The combination of MAPRE1, CEA, and AK1 yielded sensitivities of 0.483 and 0.533 at 90% specificity and sensitivities of 0.350 and 0.467 at 95% specificity for differentiating adenoma and early colorectal cancer, respectively, from healthy controls. These findings suggest that MAPRE1 can contribute to the detection of early-stage colorectal cancer and adenomas together with other biomarkers.

Induction of Lung Tumors in Mice with Urethane

In this protocol, urethane (ethyl carbamate) is used to induce lung tumors in mice. The use of urethane as an experimental carcinogen is especially attractive as it is inexpensive, relatively safe to handle, stable, and water soluble, and the protocol involves simple intraperitoneal (i.p.) injections in young mice. Urethane typically induces bronchioalveolar adenomas and, to a lesser extent, adenocarcinomas that resemble the adenocarcinoma subtype of non-small cell lung carcinoma. On a sensitive genetic background such as A/J, mice develop multiple adenomas visible on the lung surface by 25 wk, followed by the appearance of adenocarcinomas by 40 wk. Less-sensitive strains such as B6/129 develop tumors with a longer latency.

Diacetylspermine Is a Novel Prediagnostic Serum Biomarker for Non-Small-Cell Lung Cancer and Has Additive Performance With Pro-Surfactant Protein B

PURPOSE

We have investigated the potential of metabolomics to discover blood-based biomarkers relevant to lung cancer screening and early detection. An untargeted metabolomics approach was applied to identify biomarker candidates using prediagnostic sera from the Beta-Carotene and Retinol Efficacy Trial (CARET) study.

PATIENTS AND METHODS

A liquid chromatography/mass spectrometry hydrophilic interaction method designed to profile a wide range of metabolites was applied to prediagnostic serum samples from CARET participants (current or former heavy smokers), consisting of 100 patients who subsequently developed non-small-cell lung cancer (NSCLC) and 199 matched controls. A separate aliquot was used to quantify levels of pro-surfactant protein B (pro-SFTPB), a previously established protein biomarker for NSCLC. On the basis of the results from the discovery set, blinded validation of a metabolite, identified as N(1),N(12)-diacetylspermine (DAS), and pro-SFTPB was performed using an independent set of CARET prediagnostic sera from 108 patients with NSCLC and 216 matched controls.

RESULTS

Serum DAS was elevated by 1.9-fold, demonstrating significant specificity and sensitivity in the discovery set for samples collected up to 6 months before diagnosis of NSCLC. In addition, DAS significantly complemented performance of pro-SFTPB in both the discovery and validations sets, with a combined area under the curve in the validation set of 0.808 (P < .001 v pro-SFTPB).

CONCLUSION

DAS is a novel serum metabolite with significant performance in prediagnostic NSCLC and has additive performance with pro-SFTPB.

Blood-based lung cancer biomarkers identified through proteomic discovery in cancer tissues, cell lines and conditioned medium

Background

Support for early detection of lung cancer has emerged from the National Lung Screening Trial (NLST), in which low-dose computed tomography (LDCT) screening reduced lung cancer mortality by 20 % relative to chest x-ray. The US Preventive Services Task Force (USPSTF) recently recommended annual screening for the high-risk population, concluding that the benefits (life years gained) outweighed harms (false positive findings, abortive biopsy/surgery, radiation exposure). In making their recommendation, the USPSTF noted that the moderate net benefit of screening was dependent on the resolution of most false-positive results without invasive procedures. Circulating biomarkers may serve as a valuable adjunctive tool to imaging.

Results

We developed a broad-based proteomics discovery program, integrating liquid chromatography/mass spectrometry (LC/MS) analyses of freshly resected lung tumor specimens (n = 13), lung cancer cell lines (n = 17), and conditioned media collected from tumor cell lines (n = 7). To enrich for biomarkers likely to be found at elevated levels in the peripheral circulation of lung cancer patients, proteins were prioritized based on predicted subcellular localization (secreted, cell-membrane associated) and differential expression in disease samples. 179 candidate biomarkers were identified. Several markers selected for further validation showed elevated levels in serum collected from subjects with stage I NSCLC (n = 94), relative to healthy smoker controls (n = 189). An 8-marker model was developed (TFPI, MDK, OPN, MMP2, TIMP1, CEA, CYFRA 21–1, SCC) which accurately distinguished subjects with lung cancer (n = 50) from high risk smokers (n = 50) in an independent validation study (AUC = 0.775).

Conclusions

Integrating biomarker discovery from multiple sample types (fresh tissue, cell lines and conditioned medium) has resulted in a diverse repertoire of candidate biomarkers. This unique collection of biomarkers may have clinical utility in lung cancer detection and diagnoses.

Electronic supplementary material

The online version of this article (doi:10.1186/s12014-015-9090-9) contains supplementary material, which is available to authorized users.

Pleural involvement in lung cancer

The pleural space, a sterile secluded environment in the thoracic cavity, represents an attractive metastatic site for various cancers of lung, breast and gastrointestinal origins. Whereas lung and breast adenocarcinomas could invade the pleural space because of their anatomic proximity, "distant" cancers like ovarian or gastrointestinal tract adenocarcinomas may employ more active mechanisms to the same end. A pleural metastasis is often accompanied by a malignant pleural effusion (MPE), an unfavorable complication that severely restricts the quality of life and expectancy of the cancer patient. MPE is the net "product" of three different processes, namely inflammation, enhanced angiogenesis and vascular leakage. Current efforts are focusing on the identification of cancer cell autocrine (specific mutation spectra and biochemical pathways) and paracrine (cytokine and chemokine signals) characteristics as well as host features (immunological or other) that underlie the MPE phenotype. Herein we examine the pleural histology, cytology and molecular characteristics that make the pleural cavity an attractive metastasis destination for lung adenocarcinoma. Mesothelial and tumor features that may account for the tumor's ability to invade the pleural space are highlighted. Finally, possible therapeutic interventions specifically targeting MPE are discussed.

Research progress in applying proteomics technology to explore early diagnosis biomarkers of breast cancer, lung cancer and ovarian cancer

According to the China tumor registry 2013 annual report , breast cancer, lung cancer, and ovarian cancer are three common cancers in China nowadays, with high mortality due to the absence of early diagnosis technology. However, proteomics has been widespreadly implanted into every field of life science and medicine as an important part of post-genomics era research. The development of theory and technology in proteomics has provided new ideas and research fields for cancer research. Proteomics can be used not only for elucidating the mechanisms of carcinogenesis focussing on whole proteins of the tissue or cell, but also seeking the biomarkers for diagnosis and therapy of cancer. In this review, we introduce proteomics principles, covering current technology used in exploring early diagnosis biomarkers of breast cancer, lung cancer and ovarian cancer.

Identification of urine protein biomarkers with the potential for early detection of lung cancer

Lung cancer is the leading cause of cancer-related deaths and has an overall 5-year survival rate lower than 15%. Large-scale clinical trials have demonstrated a significant relative reduction in mortality in high-risk individuals with low-dose computed tomography screening. However, biomarkers capable of identifying the most at-risk population and detecting lung cancer before it becomes clinically apparent are urgently needed in the clinic. Here, we report the identification of urine biomarkers capable of detecting lung cancer. Using the well-characterized inducible Kras (G12D) mouse model of lung cancer, we identified alterations in the urine proteome in tumor-bearing mice compared with sibling controls. Marked differences at the proteomic level were also detected between the urine of patients and that of healthy population controls. Importantly, we identified 7 proteins commonly found to be significantly up-regulated in both tumor-bearing mice and patients. In an independent cohort, we showed that 2 of the 7 proteins were up-regulated in urine samples from lung cancer patients but not in those from controls. The kinetics of these proteins correlated with the disease state in the mouse model. These tumor biomarkers could potentially aid in the early detection of lung cancer.

An Autoimmune Response Signature Associated with the Development of Triple-Negative Breast Cancer Reflects Disease Pathogenesis

The repertoire of antigens associated with the development of an autoimmune response in breast cancer has relevance to detection and treatment strategies. We have investigated the occurrence of autoantibodies associated with the development of triple-negative breast cancer (TNBC) in the before diagnosis setting and in samples collected at the time of diagnosis of TNBC. Lysate arrays containing protein fractions from the TNBC MDA-MB-231 cell line were hybridized with TNBC plasmas from the Women's Health Initiative cohort, collected before clinical diagnosis and with plasmas from matched controls. An immune response directed against spliceosome and glycolysis proteins was observed with case plasmas as previously reported in estrogen receptor(+) breast cancer. Importantly, autoantibodies directed against networks involving BRCA1, TP53, and cytokeratin proteins associated with a mesenchymal/basal phenotype were distinct to TNBC before diagnosis samples. Concordant autoantibody findings were observed with mouse plasma samples collected before occurrence of palpable tumors from a C3(1)-T triple negative mouse model. Plasma samples collected at the time of diagnosis of stage II TNBC and from matched healthy controls were subjected to proteomic analysis by mass spectrometry to identify Ig-bound proteins yielding a predominance of cytokeratins, including several associated with a mesenchymal/basal phenotype among cases compared with controls. Our data provide evidence indicative of a dynamic repertoire of antigens associated with a humoral immune response reflecting disease pathogenesis in TNBC.

Proteomic Identification of Cysteine Cathepsin Substrates Shed from the Surface of Cancer Cells

Extracellular cysteine cathepsins are known to drive cancer progression, but besides degradation of extracellular matrix proteins little is known about their physiological substrates and thus the molecular mechanisms they deploy. One of the major mechanisms used by other extracellular proteases to facilitate cancer progression is proteolytic release of the extracellular domains of transmembrane proteins or ectodomain shedding. Here we show using a mass spectrometry-based approach that cathepsins L and S act as sheddases and cleave extracellular domains of CAM adhesion proteins and transmembrane receptors from the surface of cancer cells. In cathepsin S-deficient mouse pancreatic cancers, processing of these cathepsin substrates is highly reduced, pointing to an essential role of cathepsins in extracellular shedding. In addition to influencing cell migration and invasion, shedding of surface proteins by extracellular cathepsins impacts intracellular signaling as demonstrated for regulation of Ras GTPase activity, thereby providing a putative mechanistic link between extracellular cathepsin activity and cancer progression. The MS data is available via ProteomeXchange with identifier PXD002192.

Causal Modeling of Cancer-Stromal Communication Identifies PAPPA as a Novel Stroma-Secreted Factor Activating NFκB Signaling in Hepatocellular Carcinoma

Inter-cellular communication with stromal cells is vital for cancer cells. Molecules involved in the communication are potential drug targets. To identify them systematically, we applied a systems level analysis that combined reverse network engineering with causal effect estimation. Using only observational transcriptome profiles we searched for paracrine factors sending messages from activated hepatic stellate cells (HSC) to hepatocellular carcinoma (HCC) cells. We condensed these messages to predict ten proteins that, acting in concert, cause the majority of the gene expression changes observed in HCC cells. Among the 10 paracrine factors were both known and unknown cancer promoting stromal factors, the former including Placental Growth Factor (PGF) and Periostin (POSTN), while Pregnancy-Associated Plasma Protein A (PAPPA) was among the latter. Further support for the predicted effect of PAPPA on HCC cells came from both in vitro studies that showed PAPPA to contribute to the activation of NFκB signaling, and clinical data, which linked higher expression levels of PAPPA to advanced stage HCC. In summary, this study demonstrates the potential of causal modeling in combination with a condensation step borrowed from gene set analysis [Model-based Gene Set Analysis (MGSA)] in the identification of stromal signaling molecules influencing the cancer phenotype.

All living cells rely on communication with other cells to ensure their function and survival. Molecular signals are sent among cells of the same cell type and from cells of one cell type to another. In cancer, not only the cancer cells themselves are responsible for the malignancy, but also stromal (non-cancerous) cells and the molecular signals they send to cancer cells are important factors that determine the severity and outcome of the disease. Therefore, the identification of stromal signals and their influence on cancer cells is important for the development of novel treatment strategies. With a computational systems biology model of stroma-cancer cell communication, we have compiled a set of ten proteins secreted by stromal cells that shape the cancer phenotype. Most importantly, our causal analysis uncovered Pregnancy-Associated Plasma Protein A (PAPPA) as a novel paracrine inducer of the pro-tumorigenic NFκB signaling pathway. In liver cancer patients, higher levels of PAPPA protein indicate a more progressed tumor stage, confirming its clinical relevance.

Preclinical Murine Models for Lung Cancer: Clinical Trial Applications

Murine models for the study of lung cancer have historically been the backbone of preliminary preclinical data to support early human clinical trials. However, the availability of multiple experimental systems leads to debate concerning which model, if any, is best suited for a particular therapeutic strategy. It is imperative that these models accurately predict clinical benefit of therapy. This review provides an overview of the current murine models used to study lung cancer and the advantages and limitations of each model, as well as a retrospective evaluation of the uses of each model with respect to accuracy in predicting clinical benefit of therapy. A better understanding of murine models and their uses, as well as their limitations may aid future research concerning the development and implementation of new targeted therapies and chemotherapeutic agents for lung cancer.

Proteomics in cancer biomarkers discovery: challenges and applications

With the introduction of recent high-throughput technologies to various fields of science and medicine, it is becoming clear that obtaining large amounts of data is no longer a problem in modern research laboratories. However, coherent study designs, optimal conditions for obtaining high-quality data, and compelling interpretation, in accordance with the evidence-based systems biology, are critical factors in ensuring the emergence of good science out of these recent technologies. This review focuses on the proteomics field and its new perspectives on cancer research. Cornerstone publications that have tremendously helped scientists and clinicians to better understand cancer pathogenesis; to discover novel diagnostic and/or prognostic biomarkers; and to suggest novel therapeutic targets will be presented. The author of this review aims at presenting some of the relevant literature data that helped as a step forward in bridging the gap between bench work results and bedside potentials. Undeniably, this review cannot include all the work that is being produced by expert research groups all over the world.

Molecular histology of lung cancer: from targets to treatments

Lung cancer is the leading cause of cancer-related death worldwide with a 5-year survival rate of less than 15%, despite significant advances in both diagnostic and therapeutic approaches. Combined genomic and transcriptomic sequencing studies have identified numerous genetic driver mutations that are responsible for the development of lung cancer. In addition, molecular profiling studies identify gene products and their mutations which predict tumour responses to targeted therapies such as protein tyrosine kinase inhibitors and also can offer explanation for drug resistance mechanisms. The profiling of circulating micro-RNAs has also provided an ability to discriminate patients in terms of prognosis/diagnosis and high-throughput DNA sequencing strategies are beginning to elucidate cell signalling pathway mutations associated with oncogenesis, including potential stem cell associated pathways, offering the promise that future therapies may target this sub-population, preventing disease relapse post treatment and improving patient survival. This review provides an assessment of molecular profiling within lung cancer concerning molecular mechanisms, treatment options and disease-progression. Current areas of development within lung cancer profiling are discussed (i.e. profiling of circulating tumour cells) and future challenges for lung cancer treatment addressed such as detection of micro-metastases and cancer stem cells.

Molecular portraits: the evolution of the concept of transcriptome-based cancer signatures

Cancer results from dysregulation of multiple steps of gene expression programs. We review how transcriptome profiling has been widely explored for cancer classification and biomarker discovery but resulted in limited clinical impact. Therefore, we discuss alternative and complementary omics approaches.

Molecular portraits of epithelial, mesenchymal, and hybrid States in lung adenocarcinoma and their relevance to survival

Epithelial-to-mesenchymal transition (EMT) is a key process associated with tumor progression and metastasis. To define molecular features associated with EMT states, we undertook an integrative approach combining mRNA, miRNA, DNA methylation, and proteomic profiles of 38 cell populations representative of the genomic heterogeneity in lung adenocarcinoma. The resulting data were integrated with functional profiles consisting of cell invasiveness, adhesion, and motility. A subset of cell lines that were readily defined as epithelial or mesenchymal based on their morphology and E-cadherin and vimentin expression elicited distinctive molecular signatures. Other cell populations displayed intermediate/hybrid states of EMT, with mixed epithelial and mesenchymal characteristics. A dominant proteomic feature of aggressive hybrid cell lines was upregulation of cytoskeletal and actin-binding proteins, a signature shared with mesenchymal cell lines. Cytoskeletal reorganization preceded loss of E-cadherin in epithelial cells in which EMT was induced by TGFβ. A set of transcripts corresponding to the mesenchymal protein signature enriched in cytoskeletal proteins was found to be predictive of survival in independent datasets of lung adenocarcinomas. Our findings point to an association between cytoskeletal and actin-binding proteins, a mesenchymal or hybrid EMT phenotype and invasive properties of lung adenocarcinomas.

Leveraging biospecimen resources for discovery or validation of markers for early cancer detection

Validation of early detection cancer biomarkers has proven to be disappointing when initial promising claims have often not been reproducible in diagnostic samples or did not extend to prediagnostic samples. The previously reported lack of rigorous internal validity (systematic differences between compared groups) and external validity (lack of generalizability beyond compared groups) may be effectively addressed by utilizing blood specimens and data collected within well-conducted cohort studies. Cohort studies with prediagnostic specimens (eg, blood specimens collected prior to development of clinical symptoms) and clinical data have recently been used to assess the validity of some early detection biomarkers. With this background, the Division of Cancer Control and Population Sciences (DCCPS) and the Division of Cancer Prevention (DCP) of the National Cancer Institute (NCI) held a joint workshop in August 2013. The goal was to advance early detection cancer research by considering how the infrastructure of cohort studies that already exist or are being developed might be leveraged to include appropriate blood specimens, including prediagnostic specimens, ideally collected at periodic intervals, along with clinical data about symptom status and cancer diagnosis. Three overarching recommendations emerged from the discussions: 1) facilitate sharing of existing specimens and data, 2) encourage collaboration among scientists developing biomarkers and those conducting observational cohort studies or managing healthcare systems with cohorts followed over time, and 3) conduct pilot projects that identify and address key logistic and feasibility issues regarding how appropriate specimens and clinical data might be collected at reasonable effort and cost within existing or future cohorts.

Proteomic challenges: sample preparation techniques for microgram-quantity protein analysis from biological samples

Proteins regulate many cellular functions and analyzing the presence and abundance of proteins in biological samples are central focuses in proteomics. The discovery and validation of biomarkers, pathways, and drug targets for various diseases can be accomplished using mass spectrometry-based proteomics. However, with mass-limited samples like tumor biopsies, it can be challenging to obtain sufficient amounts of proteins to generate high-quality mass spectrometric data. Techniques developed for macroscale quantities recover sufficient amounts of protein from milligram quantities of starting material, but sample losses become crippling with these techniques when only microgram amounts of material are available. To combat this challenge, proteomicists have developed micro-scale techniques that are compatible with decreased sample size (100 μg or lower) and still enable excellent proteome coverage. Extraction, contaminant removal, protein quantitation, and sample handling techniques for the microgram protein range are reviewed here, with an emphasis on liquid chromatography and bottom-up mass spectrometry-compatible techniques. Also, a range of biological specimens, including mammalian tissues and model cell culture systems, are discussed.

Plasma pro-surfactant protein B and lung function decline in smokers

Plasma pro-surfactant protein B (pro-SFTPB) levels have recently been shown to predict the development of lung cancer in current and ex-smokers, but the ability of pro-SFTPB to predict measures of chronic obstructive pulmonary disease (COPD) severity is unknown. We evaluated the performance characteristics of pro-SFTPB as a biomarker of lung function decline in a population of current and ex-smokers. Plasma pro-SFTPB levels were measured in 2503 current and ex-smokers enrolled in the Pan-Canadian Early Detection of Lung Cancer Study. Linear regression was performed to determine the relationship of pro-SFTPB levels to changes in forced expiratory volume in 1 s (FEV1) over a 2-year period as well as to baseline FEV1 and the burden of emphysema observed in computed tomography (CT) scans. Plasma pro-SFTPB levels were inversely related to both FEV1 % predicted (p=0.024) and FEV1/forced vital capacity (FVC) (p<0.001), and were positively related to the burden of emphysema on CT scans (p<0.001). Higher plasma pro-SFTPB levels were also associated with a more rapid decline in FEV1 at 1 year (p=0.024) and over 2 years of follow-up (p=0.004). Higher plasma pro-SFTPB levels are associated with increased severity of airflow limitation and accelerated decline in lung function. Pro-SFTPB is a promising biomarker for COPD severity and progression.

Analysis of AKT and ERK1/2 protein kinases in extracellular vesicles isolated from blood of patients with cancer

Background

Extracellular vesicles (EVs) are small nanometre-sized vesicles that are circulating in blood. They are released by multiple cells, including tumour cells. We hypothesized that circulating EVs contain protein kinases that may be assessed as biomarkers during treatment with tyrosine kinase inhibitors.

Methods

EVs released by U87 glioma cells, H3255 and H1650 non-small-cell lung cancer (NSCLC) cells were profiled by tandem mass spectrometry. Total AKT/protein kinase B and extracellular signal regulated kinase 1/2 (ERK1/2) levels as well as their relative phosphorylation were measured by western blot in isogenic U87 cells with or without mutant epidermal growth factor receptor (EGFRvIII) and their corresponding EVs. To assess biomarker potential, plasma samples from 24 healthy volunteers and 42 patients with cancer were used.

Results

In total, 130 different protein kinases were found to be released in EVs including multiple drug targets, such as mammalian target of rapamycin (mTOR), AKT, ERK1/2, AXL and EGFR. Overexpression of EGFRvIII in U87 cells results in increased phosphorylation of EGFR, AKT and ERK1/2 in cells and EVs, whereas a decreased phosphorylation was noted upon treatment with the EGFR inhibitor erlotinib. EV samples derived from patients with cancer contained significantly more protein (p=0.0067) compared to healthy donors. Phosphorylation of AKT and ERK1/2 in plasma EVs from both healthy donors and patients with cancer was relatively low compared to levels in cancer cells. Preliminary analysis of total AKT and ERK1/2 levels in plasma EVs from patients with NSCLC before and after sorafenib/metformin treatment (n=12) shows a significant decrease in AKT levels among patients with a favourable treatment response (p<0.005).

Conclusion

Phosphorylation of protein kinases in EVs reflects their phosphorylation in tumour cells. Total AKT protein levels may allow monitoring of kinase inhibitor responses in patients with cancer.

Respiratory proteomics: from descriptive studies to personalized medicine

Respiratory diseases are highly prevalent and affect humankind worldwide, causing extensive morbidity and mortality with the environment playing an important role. Given the complex structure of the airways, sophisticated tools are required for early diagnosis; initial symptoms are nonspecific, and the clinical diagnosis is made frequently late. Over the past few years, proteomics has made high technological progress in mass-spectrometry-based protein identification and has allowed us to gain new insights into disease mechanisms and identify potential novel therapeutic targets. This review will highlight the contributions of proteomics toward the understanding of the respiratory proteome listing potential biomarkers and its potential application to the clinic. We also outline the contributions of proteomics to creating a personalized approach in respiratory medicine.

Proteomic signatures associated with p53 mutational status in lung adenocarcinoma

p53 is commonly mutated in lung adenocarcinoma. Mutant p53 loses wild-type function and some missense mutations further acquire oncogenic functions, while p53 wild-type may also induce pro-survival signaling. Therefore identification of signatures based on p53 mutational status has relevance to our understanding of p53 signaling pathways in cancer and identification of new therapeutic targets. To this end, we compared proteomic profiles of three cellular compartments (whole-cell extract, cell surface, and media) from 28 human lung adenocarcinoma cell lines that differ based on p53 mutational status. In total, 11,598, 11,569, and 9090 protein forms were identified in whole-cell extract, cell surface, and media, respectively. Bioinformatic analysis revealed that representative pathways associated with epithelial adhesion, immune and stromal cells, and mitochondrial function were highly significant in p53 missense mutations, p53 loss and wild-type p53 cell lines, respectively. Of note, mRNA levels of peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1-α), a transcription coactivator that promotes mitochondrial oxidative phosphorylation and mitochondrial biogenesis, was substantially higher in p53 wild-type cell lines compared to either cell lines with p53 loss or with missense mutation. Small interfering RNA targeting PGC1-α inhibited cell proliferation in p53 wild-type cell lines, indicative of PGC1-α and its downstream molecules as potential therapeutic targets in p53 wild-type lung adenocarcinoma.

Opportunities and challenges of proteomics in pediatric patients: circulating biomarkers after hematopoietic stem cell transplantation as a successful example

Biomarkers have the potential to improve diagnosis and prognosis, facilitate-targeted treatment, and reduce health care costs. Thus, there is great hope that biomarkers will be integrated in all clinical decisions in the near future. A decade ago, the biomarker field was launched with great enthusiasm because MS revealed that blood contains a rich library of candidate biomarkers. However, biomarker research has not yet delivered on its promise due to several limitations: (i) improper sample handling and tracking as well as limited sample availability in the pediatric population, (ii) omission of appropriate controls in original study designs, (iii) lability and low abundance of interesting biomarkers in blood, and (iv) the inability to mechanistically tie biomarker presence to disease biology. These limitations as well as successful strategies to overcome them are discussed in this review. Several advances in biomarker discovery and validation have been made in hematopoietic stem cell transplantation, the current most effective tumor immunotherapy, and these could serve as examples for other conditions. This review provides fresh optimism that biomarkers clinically relevant in pediatrics are closer to being realized based on: (i) a uniform protocol for low-volume blood collection and preservation, (ii) inclusion of well-controlled independent cohorts, (iii) novel technologies and instrumentation with low analytical sensitivity, and (iv) integrated animal models for exploring potential biomarkers and targeted therapies.

Statistical detection of quantitative protein biomarkers provides insights into signaling networks deregulated in acute myeloid leukemia

The increasing coverage and sensitivity of LC-MS/MS-based proteomics have expanded its applications in systems medicine. In particular, label-free quantitation approaches are enabling biomarker discovery in terms of statistical comparison of proteomic profiles across large numbers of clinical samples. However, it still remains poorly understood how much protein markers can add novel insights compared to markers derived from mRNA transcriptomic profiling. Using paired label-free LC-MS/MS and gene expression microarray measurements from primary samples of patients with acute myeloid leukemia (AML), we demonstrate here that while the quantitative proteomic and transcriptomic profiles were highly correlated, in general, the marker panels showing statistically significant expression changes across the disease and healthy groups were profoundly different between protein and mRNA levels. In particular, the proteomic assay enabled unique links to known leukemic processes, which were missed when using the transcriptomic profiling alone, as well as identified additional links to metabolic regulators and chromatin remodelers, such as GPX1, fumarate hydratase, and SET oncogene, which have subsequently been evaluated in independent AML samples. Overall, these results highlighted the complementary and informative view obtained from the quantitative LC-MS/MS approach into the AML deregulated signaling networks.

Modeling lung cancer evolution and preclinical response by orthotopic mouse allografts

Cancer evolution is a process that is still poorly understood because of the lack of versatile in vivo longitudinal studies. By generating murine non-small cell lung cancer (NSCLC) orthoallobanks and paired primary cell lines, we provide a detailed description of an in vivo, time-dependent cancer malignization process. We identify the acquisition of metastatic dissemination potential, the selection of co-driver mutations, and the appearance of naturally occurring intratumor heterogeneity, thus recapitulating the stochastic nature of human cancer development. This approach combines the robustness of genetically engineered cancer models with the flexibility of allograft methodology. We have applied this tool for the preclinical evaluation of therapeutic approaches. This system can be implemented to improve the design of future treatments for patients with NSCLC.

New discoveries of old SON: a link between RNA splicing and cancer

The SON protein is a ubiquitously expressed DNA- and RNA-binding protein primarily localized to nuclear speckles. Although several early studies implicated SON in DNA-binding, tumorigenesis and apoptosis, functional significance of this protein had not been recognized until recent studies discovered SON as a novel RNA splicing co-factor. During constitutive RNA splicing, SON ensures efficient intron removal from the transcripts containing suboptimal splice sites. Importantly, SON-mediated splicing is required for proper processing of selective transcripts related to cell cycle, microtubules, centrosome maintenance, and genome stability. Moreover, SON regulates alternative splicing of RNAs from the genes involved in apoptosis and epigenetic modification. In addition to the role in RNA splicing, SON has an ability to suppress transcriptional activation at certain promoter/enhancer DNA sequences. Considering the multiple SON target genes which are directly involved in cell proliferation, genome stability and chromatin modifications, SON is an emerging player in gene regulation during cancer development and progression. Here, we summarize available information from several early studies on SON, and highlight recent discoveries describing molecular mechanisms of SON-mediated gene regulation. We propose that our future effort on better understanding of diverse SON functions would reveal novel targets for cancer therapy.

Estimation of treatment policies based on functional predictors

Biosignatures such as brain scans, mass spectrometry, or gene expression profiles might one day be used to guide treatment selection and improve outcomes. This article develops a way of estimating optimal treatment policies based on data from randomized clinical trials by interpreting patient biosignatures as functional predictors. A flexible functional regression model is used to represent the treatment effect and construct the estimated policy. The effectiveness of the estimated policy is assessed by furnishing prediction intervals for the mean outcome when all patients follow the policy. The validity of these prediction intervals is established under mild regularity conditions on the functional regression model. The performance of the proposed approach is evaluated in numerical studies.

A search for novel cancer/testis antigens in lung cancer identifies VCX/Y genes, expanding the repertoire of potential immunotherapeutic targets

Cancer/testis (CT) antigens are potential immunotherapeutic targets in cancer. However, the expression of particular antigens is limited to a subset of tumors of a given type. Thus, there is a need to identify antigens with complementary expression patterns for effective therapeutic intervention. In this study, we searched for genes that were distinctly expressed at a higher level in lung tumor tissue and the testes compared with other nontumor tissues and identified members of the VCX/Y gene family as novel CT antigens. VCX3A, a member of the VCX/Y gene family, was expressed at the protein level in approximately 20% of lung adenocarcinomas and 35% of squamous cell carcinomas, but not expressed in normal lung tissues. Among CT antigens with concordant mRNA and protein expression levels, four CT antigens, XAGE1, VCX, IL13RA2, and SYCE1, were expressed, alone or in combination, in about 80% of lung adenocarcinoma tumors. The CT antigen VCX/Y gene family broadens the spectrum of CT antigens expressed in lung adenocarcinomas for clinical applications.

Systems biology approaches to develop innovative strategies for lung cancer therapy

Lung cancer (LC) is a number one killer of cancer-related death among men and women worldwide. Major advances have been made in the diagnosis, staging and use of surgery for LC, but systemic chemotherapy and radiotherapy alone or in combination with some targeted agents remains the core treatment of advanced LC. Unfortunately, in spite of improved diagnosis, surgical methods and new treatments, mortality is still extremely high among LC patients. To understand the precise functioning of signaling pathways associated with resistance to current treatments in LC, as well as to identify novel treatment regimens, a holistic approach to analyze signaling networks should be applied. Here, we describe systems biology-based approaches to generate biomarkers and novel therapeutic targets in LC, as well as how this may contribute to personalized treatment for this malignancy.

From mice to men: GEMMs as trial patients for new NSCLC therapies

Given the large socio-economic burden of cancer, there is an urgent need for in vivo animal cancer models that can provide a rationale for personalised therapeutic regimens that are translatable to the clinic. Recent developments in establishing mouse models that closely resemble human lung cancers involve the application of genetically engineered mouse models (GEMMs) for use in drug efficacy studies or to guide patient therapy. Here, we review recent applications of GEMMs in non-small cell lung cancer research for drug development and their potential in aiding biomarker discovery and understanding of biological mechanisms behind clinical outcomes and drug interactions.

Serum-based protein biomarkers for detection of lung cancer

Lung cancer is one of the most common cancers in terms of both incidence and mortality.The major reasons for the increasing number of deaths from lung cancer are late detection and lack of effective therapies. To improve our understanding of lung cancer biology, there is urgent need for blood-based, non-invasive molecular tests to assist in its detection in a cost-effective manner at an early stage when curative interventions are still possible. Recent advances in proteomic technology have provided extensive, high throughput analytical tools for identification, characterization and functional studies of proteomes. Changes in protein expression patterns in response to stimuli can serve as indicators or biomarkers of biological and pathological processes as well as physiological and pharmacological responses to drug treatment, thus aiding in early diagnosis and prognosis of disease. However, only a few biomarkers have been approved by the FDA to date for screening and diagnostic purposes. This review provides a brief overview of currently available proteomic techniques, their applications and limitations and the current state of knowledge about important serum biomarkers in lung cancer and their potential value as prognostic and diagnostic tools.

Mass spectrometry-based plasma proteomics: state of the art and future outlook

Mass spectrometry-based plasma proteomics is a field where intense research has been performed during the last decade. Being closely linked to biomarker discovery, the field has received a fair amount of criticism, mostly due to the low number of novel biomarkers reaching the clinic. However, plasma proteomics is under gradual development with improvements on fractionation methods, mass spectrometry instrumentation and analytical approaches. These recent developments have contributed to the revival of plasma proteomics. The goal of this review is to summarize these advances, focusing in particular on fractionation methods, both for targeted and global mass spectrometry-based plasma analysis.

Risk-reduction strategies to expand radon care planning with vulnerable groups

OBJECTIVES

Radon is the second leading cause of lung cancer in the United States and the leading cause of lung cancer among nonsmokers. Residential radon is the cause of approximately 21,000 U.S. lung cancer deaths each year. Dangerous levels of radon are just as likely to be found in low-rise apartments and townhomes as single-family homes in the same area. The preferred radon mitigation strategy can be expensive and requires structural modifications to the home. The public health nurse (PHN) needs a collection of low-cost alternatives when working with low-income families or families who rent their homes.

METHOD

A review of the literature was performed to identify evidence-based methods to reduce radon risk with vulnerable populations.

RESULTS

Fourteen recommendations for radon risk reduction were categorized into four strategies. Nine additional activities for raising awareness and increasing testing were also included.

DISCUSSION

The results pair the PHN with practical interventions and the underlying rationale to develop radon careplans with vulnerable families across housing types. The PHN has both the competence and the access to help families reduce their exposure to this potent carcinogen.

Mouse to human blood-based cancer biomarker discovery strategies

There is an urgent need for noninvasive molecular tests to assist in the detection of cancers. There is additionally a need for prognostic and predictive markers and for monitoring for disease recurrence. The improved understanding of molecular features of common cancers and the availability of genetically engineered mouse models (GEMMs) of cancer have resulted in increased interest in the application of mouse models to the discovery of cancer biomarkers relevant to humans. Unlike humans, mouse models allow sampling of tumor and host tissues and biological fluids at defined time points in the course of tumor development and progression. Interrogation of the genome, transcriptome, proteome, and metabolome of tumors and biological fluids from mouse models engineered to recapitulate human tumors makes it possible to apply a systems approach to define biomarker signatures from the earliest stages of tumor development to advanced stages and metastasis and signatures reflective of driver genes and pathways.

Predicting early intrahepatic recurrence of hepatocellular carcinoma after microwave ablation using SELDI-TOF proteomic signature

BACKGROUND/AIMS

Despite great progress in the treatment of hepatocellular carcinoma (HCC) over the last-decade, intrahepatic recurrence is still the most frequent serious adverse event after all the treatments including microwave ablation. This study aimed to predict early recurrence of HCC after microwave ablation using serum proteomic signature.

METHODS

After curative microwave ablation of HCC, 86 patients were followed-up for 1 year. Serum samples were collected before microwave ablation. The mass spectra of proteins were generated using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). Serum samples from 50 patients were randomly selected as a training set and for biomarkers discovery and model development. The remaining serum samples were categorized for validation of the algorithm.

RESULTS

According to preablation serum protein profiling obtained from the 50 HCC samples in the training set, nine significant differentially-expressed proteins were detected in the serum samples between recurrent and non-recurrent patients. Decision classification tree combined with three candidate proteins with m/z values of 7787, 6858 and 6646 was produced using Biomarker Patterns Software with sensitivity of 85.7% and specificity of 88.9% in the training set. When the SELDI marker pattern was tested with the blinded testing set, it yielded a sensitivity of 80.0%, a specificity of 88.5% and a positive predictive value of 86.1%.

CONCLUSIONS

Differentially-expressed protein peaks in preablation serum screened by SELDI are associated with prognosis of HCC. The decision classification tree is a potential tool in predicting early intrahepatic recurrence in HCC patients after microwave ablation.

Pro-surfactant protein B as a biomarker for lung cancer prediction

PURPOSE

Preliminary studies have identified pro-surfactant protein B (pro-SFTPB) to be a promising blood biomarker for non-small-cell lung cancer. We conducted a study to determine the independent predictive potential of pro-SFTPB in identifying individuals who are subsequently diagnosed with lung cancer.

PATIENTS AND METHODS

Pro-SFTPB levels were measured in 2,485 individuals, who enrolled onto the Pan-Canadian Early Detection of Lung Cancer Study by using plasma sample collected at the baseline visit. Multivariable logistic regression models were used to evaluate the predictive ability of pro-SFTPB in addition to known lung cancer risk factors. Calibration and discrimination were evaluated, the latter by an area under the receiver operating characteristic curve (AUC). External validation was performed with samples collected in the Carotene and Retinol Efficacy Trial (CARET) participants using a case-control study design.

RESULTS

Adjusted for age, sex, body mass index, personal history of cancer, family history of lung cancer, forced expiratory volume in one second percent predicted, average number of cigarettes smoked per day, and smoking duration, pro-SFTPB (log transformed) had an odds ratio of 2.220 (95% CI, 1.727 to 2.853; P < .001). The AUCs of the full model with and without pro-SFTPB were 0.741 (95% CI, 0.696 to 0.783) and 0.669 (95% CI, 0.620 to 0.717; difference in AUC P < .001). In the CARET Study, the use of pro-SFPTB yielded an AUC of 0.683 (95% CI, 0.604 to 0.761).

CONCLUSION

Pro-SFTPB in plasma is an independent predictor of lung cancer and may be a valuable addition to existing lung cancer risk prediction models.

Characterization of Niemann-Pick Type C2 protein expression in multiple cancers using a novel NPC2 monoclonal antibody

Niemann-Pick Type C2 (NPC2) plays an important role in the regulation of intracellular cholesterol homeostasis via direct binding with free cholesterol. However, little is known about the significance of NPC2 in cancer. In this study, we have pinpointed the impact of various different cancers on NPC2 expression. A series of anti-NPC2 monoclonal antibodies (mAbs) with the IgG2a isotype were generated and peptide screening demonstrated that the reactive epitope were amino acid residues 31-40 of the human NPC2 protein. The specificity of these mAbs was confirmed by Western blotting using shRNA mediated knock-down of NPC2 in human SK-Hep1 cells. By immunohistochemical staining, NPC2 is expressed in normal kidney, liver, breast, colon, lung, esophageal, uterine cervical, pancreatic and stomach tissue. Strong expression of NPC2 was found in the distal and proximal convoluted tubule of kidney and the hepatocytes of liver. Normal esophageal, uterine cervical, pancreatic, stomach, breast, colon and lung tissue stained moderately to weakly. When compared to their normal tissue equivalents, NPC2 overexpression was observed in cancers of the breast, colon and lung. Regarding to breast cancer, NPC2 up-regulation is associated with estrogen receptor (-), progesterone receptor (-) and human epidermal growth factor receptor (+). On the other hand, NPC2 was found to be down-regulated in renal cell carcinoma, liver cirrhosis and hepatoma tissues. By antigen-capture enzyme immunoassay ELISA, the serum NPC2 is increased in patients with cirrhosis and liver cancer. According to western blot data, the change of glycosylated pattern of NPC2 in serum is associated with cirrhosis and liver cancer. To the best of our knowledge, this is the first comprehensive immunohistochemical and serological study investigating the expression of NPC2 in a variety of different human cancers. These novel monoclonal antibodies should help with elucidating the roles of NPC2 in tumor development, especially in liver and breast cancers.

The complexity of thyroid transcription factor 1 with both pro- and anti-oncogenic activities

After the original identification of thyroid transcription factor 1 (TTF-1 or NKX2-1) biochemical activity as a transcriptional regulator of thyroglobulin in 1989, the bulk of the ensuing research has concentrated on elucidating the roles of NKX2-1 in the development of lung and thyroid tissues. Motivated by its specific expression pattern, pathologists adopted the NKX2-1 immunoreactivity to distinguish pulmonary from nonpulmonary nonthyroid adenocarcinomas. Interestingly, the concept of NKX2-1 as an active participant in lung tumorigenesis did not take hold until 2007. This minireview contrasts the recent advancements of NKX2-1-related observations primarily in the realm of pulmonary malignancies.

Circulating pro-surfactant protein B as a risk biomarker for lung cancer

BACKGROUND

Our prior studies of lung cancer suggested that a novel biomarker (pro-surfactant protein B or pro-SFTPB) might serve as a predictive marker for this disease. We aimed to determine the potential use of pro-SFTPB for distinguishing lung cancer cases from matched controls as a risk marker.

METHODS

Study subjects were drawn from the longitudinal Physicians' Health Study (PHS). Cases (n = 188) included individuals who were cancer-free at study enrollment but developed lung cancer during follow-up. Controls (n = 337) were subjects who did not develop lung cancer. Cases and controls were matched on date of study enrollment, age at enrollment, and smoking status and amount. Baseline plasma samples drawn at enrollment were analyzed for pro-SFTPB using ELISA to detect differences in protein expression levels for cases and controls.

RESULTS

Pro-SFTPB nondetectable status was significantly associated with lung cancer risk [OR = 5.88; 95% confidence interval (CI) 1.24-27.48]. Among subjects with detectable levels of the protein, increasing plasma concentration of pro-SFTPB was associated with higher lung cancer risk (OR = 1.41 per unit increase in log pro-SFTPB; 95% CI 1.08-1.84).

CONCLUSION

These results suggest a nonlinear, J-shaped association between plasma pro-SFTPB levels and lung cancer risk, with both nondetectable and higher levels of the marker being associated with lung cancer.

IMPACT

These results show promise of a risk marker that could contribute to predicting risk for lung cancer development and to narrowing the high-risk population for low-dose computed tomography screening.

Molecular biomarkers for future screening of lung cancer

The Landmark National Lung Screening Trial established the potential for low dose CT screening (LDCT) to reduce lung cancer-specific mortality in high-risk patients as defined by smoking history and age. However, the prevalence of lung cancer in asymptomatic smokers selected based on the NLST criteria is low. Recent advances have facilitated biomarker discovery for early diagnosis of lung cancer through the analysis of surrogate tissues, including airway epithelium, sputum, exhaled breath, and blood. Although a number of candidate diagnostic biomarkers have been described, none have been validated for use in the clinical setting. The NLST ACRIN biomarker repository is a valuable resource of annotated biological specimens that were collected during the NLST trial, which has the potential to facilitate validation of candidate biomarkers for early diagnosis identified in discovery trials. It will be important to perform retrospective and prospective analysis of biomarkers to screen for lung cancer. The review below summarizes some of our understanding of biomarkers in screening.

Glycoproteomic analysis of bronchoalveolar lavage (BAL) fluid identifies tumor-associated glycoproteins from lung adenocarcinoma

Cytological examination of cells from bronchoalveolar lavage (BAL) is commonly used for the diagnosis of lung cancer. Proteins released from lung cancer cells into BAL may serve as biomarkers for cancer detection. In this study, N-glycoproteins in eight cases of BAL fluid, as well as eight lung adenocarcinoma tissues and eight tumor-matched normal lung tissues, were analyzed using the solid-phase extraction of N-glycoprotein (SPEG), iTRAQ labeling, and liquid chromatography tandem mass spectrometry (LC-MS/MS). Of 80 glycoproteins found in BAL specimens, 32 were identified in both cancer BAL and cancer tissues, with levels of 25 glycoproteins showing at least a 2-fold difference between cancer and benign BAL. Among them, eight glycoproteins showed greater than 2-fold elevations in cancer BAL, including Neutrophil elastase (NE), Integrin alpha-M, Cullin-4B, Napsin A, lysosome-associated membrane protein 2 (LAMP2), Cathepsin D, BPI fold-containing family B member 2, and Neutrophil gelatinase-associated lipocalin. The levels of Napsin A in cancer BAL were further verified in independently collected 39 BAL specimens using an ELISA assay. Our study demonstrates that potential protein biomarkers in BAL fluid can be detected and quantified.

Association of epidermal growth factor receptor mutations with human papillomavirus 16/18 E6 oncoprotein expression in non-small cell lung cancer

BACKGROUND

Lung cancers in women, in nonsmokers, and in patients with adenocarcinoma from Asia have more prevalent mutations in the epidermal growth factor receptor (EGFR) gene than their counterparts. However, the etiology of EGFR mutations in this population remains unclear. The authors hypothesized that the human papillomavirus (HPV) type 16/18 (HPV16/18) E6 oncoprotein may contribute to EGFR mutations in Taiwanese patients with lung cancer.

METHODS

One hundred fifty-one tumors from patients with lung cancer were enrolled to determine HPV16/18 E6 and EGFR mutations using immunohistochemistry and direct sequencing, respectively. Levels of 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxo-dG) in lung tumors and cells were evaluated using immunohistochemistry and liquid chromatography-mass spectrometry/mass spectrometry. An supF mutagenesis assay was used to determine H2 O2 -induced mutation rates of lung cancer cells with or without E6 expression.

RESULTS

Patients with E6-positive tumors had a greater frequency of EGFR mutations than those with E6-negative tumors (41% vs 20%; P = .006). Levels of 8-oxo-dG were correlated with EGFR mutations (36% vs 16%; P = .012). Two stable clones of E6-overexpressing H157 and CL-3 cells were established for the supF mutagenesis assay. The data indicated that the cells with high E6 overexpression had higher H2 O2 -induced SupF gene mutation rates compared with the cells that expressed lower levels of E6 and compared with vector control cells.

CONCLUSIONS

HPV16/18 E6 may contribute in part to EGFR mutations in lung cancer, at least in the Taiwanese population.

An iPSC line from human pancreatic ductal adenocarcinoma undergoes early to invasive stages of pancreatic cancer progression

Pancreatic ductal adenocarcinoma (PDAC) carries a dismal prognosis and lacks a human cell model of early disease progression. When human PDAC cells are injected into immunodeficient mice, they generate advanced-stage cancer. We hypothesized that if human PDAC cells were converted to pluripotency and then allowed to differentiate back into pancreatic tissue, they might undergo early stages of cancer. Although most induced pluripotent stem cell (iPSC) lines were not of the expected cancer genotype, one PDAC line, 10-22 cells, when injected into immunodeficient mice, generated pancreatic intraepithelial neoplasia (PanIN) precursors to PDAC that progressed to the invasive stage. The PanIN-like cells secrete or release proteins from many genes that are known to be expressed in human pancreatic cancer progression and that predicted an HNF4α network in intermediate-stage lesions. Thus, rare events allow iPSC technology to provide a live human cell model of early pancreatic cancer and insights into disease progression.

Chip-based nLC-TOF-MS is a highly stable technology for large-scale high-throughput analyses

Many studies focused on the discovery of novel biomarkers for the diagnosis and treatment of disease states are facilitated by mass spectrometry-based technology. HPLC coupled to mass spectrometry is widely used; miniaturization of this technique using nano-liquid chromatography (LC)-mass spectrometry (MS) usually results in better sensitivity, but is associated with limited repeatability. The recent introduction of chip-based technology has significantly improved the stability of nano-LC-MS, but no substantial studies to verify this have been performed. To evaluate the temporal repeatability of chip-based nano-LC-MS analyses, N-glycans released from a serum sample were repeatedly analyzed using nLC-PGC-chip-TOF-MS on three non-consecutive days. With an average inter-day coefficient of variation of 4 %, determined on log10-transformed integrals, the repeatability of the system is very high. Overall, chip-based nano-LC-MS appears to be a highly stable technology, which is suitable for the profiling of large numbers of clinical samples for biomarker discovery.