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.     

A Highly Efficient Gene Expression Programming (GEP) Model for Auxiliary Diagnosis of Small Cell Lung Cancer

Background

Lung cancer is an important and common cancer that constitutes a major public health problem, but early detection of small cell lung cancer can significantly improve the survival rate of cancer patients. A number of serum biomarkers have been used in the diagnosis of lung cancers; however, they exhibit low sensitivity and specificity.

Methods

We used biochemical methods to measure blood levels of lactate dehydrogenase (LDH), C-reactive protein (CRP), Na⁺, Cl^-, carcino-embryonic antigen (CEA), and neuron specific enolase (NSE) in 145 small cell lung cancer (SCLC) patients and 155 non-small cell lung cancer and 155 normal controls. A gene expression programming (GEP) model and Receiver Operating Characteristic (ROC) curves incorporating these biomarkers was developed for the auxiliary diagnosis of SCLC.

Results

After appropriate modification of the parameters, the GEP model was initially set up based on a training set of 115 SCLC patients and 125 normal controls for GEP model generation. Then the GEP was applied to the remaining 60 subjects (the test set) for model validation. GEP successfully discriminated 281 out of 300 cases, showing a correct classification rate for lung cancer patients of 93.75% (225/240) and 93.33% (56/60) for the training and test sets, respectively. Another GEP model incorporating four biomarkers, including CEA, NSE, LDH, and CRP, exhibited slightly lower detection sensitivity than the GEP model, including six biomarkers. We repeat the models on artificial neural network (ANN), and our results showed that the accuracy of GEP models were higher than that in ANN. GEP model incorporating six serum biomarkers performed by NSCLC patients and normal controls showed low accuracy than SCLC patients and was enough to prove that the GEP model is suitable for the SCLC patients.

Conclusion

We have developed a GEP model with high sensitivity and specificity for the auxiliary diagnosis of SCLC. This GEP model has the potential for the wide use for detection of SCLC in less developed regions.     

Small-cell lung cancer brain metastasis: From molecular mechanisms to diagnosis and treatment

Lung cancer is the most malignant human cancer worldwide, also with the highest incidence rate. However, small-cell lung cancer (SCLC) accounts for 14 % of all lung cancer cases. Approximately 10 % of patients with SCLC have brain metastasis at the time of diagnosis, which is the leading cause of death of patients with SCLC worldwide. The median overall survival is only 4.9 months, and a long-tern cure exists for patients with SCLC brain metastasis due to limited common therapeutic options. Recent studies have enhanced our understanding of the molecular mechanisms leading to meningeal metastasis, and multimodality treatments have brought new hopes for a better cure for the disease. This review aimed to offer an insight into the cellular processes of different metastatic stages of SCLC revealed by the established animal models, and into the major diagnostic methods of SCLC. Additionally, it provided in-depth information on the recent advances in SCLC treatments, and highlighted several new models and biomarkers with promises to improve the prognosis of SCLC.     

Autoantibody biomarker opens a new gateway for cancer diagnosis

The list of cancer markers of current interest has grown considerably, but none of the markers used in clinical work is a true tumor marker. These cancer biomarkers are based on the determination of tumor antigens. Here, we report a single method of autoantibody enzyme immunoassay (EIA) screens for a spectrum of serum tumor markers. A comparison of the autoantibody-based EIA to conventional antigen EIA kits, using receiver operating characteristic (ROC) plots, showed that the autoantibody EIA can significantly enhance the sensitivity and specificity of tumor markers. The detection of serum autoantibodies for a spectrum of serum tumor markers, as demonstrated here, suggests that most, if not all, serum cancer biomarkers produce autoantibodies. A unique autoantibody biomarker screening method, as presented here, might therefore facilitate achieving the accurate and early diagnosis of cancer.     

Identification of biomarkers for colorectal cancer through proteomics-based approaches

The early detection of colorectal cancer is one of the great challenges in the battle against this disease. However, owing to its heterogeneous character, single markers are not likely to provide sufficient diagnostic power to be used in colorectal cancer population screens. This review provides an overview of recent studies aimed at the discovery of new diagnostic protein markers through proteomics-based approaches. It indicates that studies that start with the proteomic analysis of tumor tissue or tumor cell lines (near the source) have a high potential to yield novel and colorectal cancer-specific biomarkers. In the next step, the diagnostic accuracy of these candidate markers can be assessed by a targeted ELISA assay using serum from colorectal cancer patients and healthy controls. Instead, direct proteomic analysis of serum yields predominantly secondary markers composed of fragments of abundant serum proteins that may be associated with tumor-associated protease activity, and alternatively, immunoproteomic analysis of the serum antibody repertoire provides a valuable tool to identify the molecular imprint of colorectal cancer-associated antigens directly from patient serum samples. The latter approach also allows a relatively easy translation into targeted assays. Eventually, multimarker assays should be developed to reach a diagnostic accuracy that meets the stringent criteria for colorectal cancer screening at the population level.     

应用双向热循环消减SELEX技术筛选肺癌血清核酸适配体

肺癌是发病率和死亡率较高的恶性肿瘤。现阶段,用于肺癌早期诊断的血清肿瘤标志物因其特异性与敏感性均较低,严重影响肺癌的临床诊断和治疗。本文用双向热循环消减指数富集的配基进化(systematic evolution of ligands by exponential enrichment, SELEX)技术,筛选肺癌和非癌血清标志物的核酸适配体,建立肺癌的检测方法,提高诊断和治疗效率。实验用环氧基琼脂磁珠为筛选介质,以非癌混合血清、肺癌混合血清作为双向靶标。应用热循环消减SELEX技术,经19轮筛选分别获得非癌和肺癌血清的特异性核酸适配体。通过高通量测序,得到 40条非癌核酸适配体序列和 41条肺癌核酸适配体序列。从肺癌与非癌血清特异性核酸适配体序列中分别挑选出高丰度的 4条序列,合成后制成检测试剂,经临床血清验证,阳性率为 90%。该检测方法检测灵敏度高,为肺癌的早期诊断和治疗提供了新的分子识别元件。     

Proteomic contributions to personalized cancer care

Cancer impacts each patient and family differently. Our current understanding of the disease is primarily limited to clinical hallmarks of cancer, but many specific molecular mechanisms remain elusive. Genetic markers can be used to determine predisposition to tumor development, but molecularly targeted treatment strategies that improve patient prognosis are not widely available for most cancers. Individualized care plans, also described as personalized medicine, still must be developed by understanding and implementing basic science research into clinical treatment. Proteomics holds great promise in contributing to the prevention and cure of cancer because it provides unique tools for discovery of biomarkers and therapeutic targets. As such, proteomics can help translate basic science discoveries into the clinical practice of personalized medicine. Here we describe how biological mass spectrometry and proteome analysis interact with other major patient care and research initiatives and present vignettes illustrating efforts in discovery of diagnostic biomarkers for ovarian cancer, development of treatment strategies in lung cancer, and monitoring prognosis and relapse in multiple myeloma patients.     

Integrated Glycoproteomics Demonstrates Fucosylated Serum Paraoxonase 1 Alterations in Small Cell Lung Cancer

Small cell lung cancer (SCLC) is an aggressive type of lung cancer, and the detection of SCLCs at an early stage is necessary for successful therapy and for improving cancer survival rates. Fucosylation is one of the most common glycosylation-based modifications. Increased levels of fucosylation have been reported in a number of pathological conditions, including cancers. In this study, we aimed to identify and validate the aberrant and selective fucosylated glycoproteins in the sera of patients with SCLC. Fucosylated glycoproteins were enriched by the Aleuria aurantia lectin column after serum albumin and IgG depletion. In a narrowed down and comparative data analysis of both label-free proteomics and isobaric peptide-tagging chemistry iTRAQ approaches, the fucosylated glycoproteins were identified as up- or down-regulated in the sera of limited disease and extensive disease stage patients with SCLC. Verification was performed by multiple reaction monitoring-mass spectrometry to select reliable markers. Four fucosylated proteins, APCS, C9, SERPINA4, and PON1, were selected and subsequently validated by hybrid A. aurantia lectin ELISA (HLE) and Western blotting. Compared with Western blotting, the HLE analysis of these four proteins produced more optimal diagnostic values for SCLC. The PON1 protein levels were significantly reduced in the sera of patients with SCLC, whereas the fucosylation levels of PON1 were significantly increased. Fucosylated PON1 exhibited an area under curve of 0.91 for the extensive disease stage by HLE, whereas the PON1 protein levels produced an area under curve of 0.82 by Western blot. The glycan structural analysis of PON1 by MS/MS identified a biantennary fucosylated glycan modification consisting of a core + 2HexNAc + 1Fuc at increased levels in the sera of patients with SCLC. In addition, the PON1 levels were decreased in the sera of the Lewis lung carcinoma lung cancer mouse model that we examined. Our data suggest that fucosylated protein biomarkers, such as PON1, and their fucosylation levels and patterns can serve as diagnostic and prognostic serological markers for SCLC.Lung cancer is the most common cause of cancer death worldwide, with over one million cases annually (World Health Organization, economics of tobacco control). Lung cancer can be divided into four major histological subtypes as follows: adenocarcinoma, squamous cell carcinoma, large cell carcinoma, and small cell carcinoma (1). Small cell lung cancer (SCLC)¹ is distinguishable from the other three histological subtypes (non-SCLC) by its distinct histological appearance (1, 2). SCLC is a neuroendocrine lung cancer subtype, which accounts for ∼20% of all lung cancer cases (3). SCLC is an aggressive malignancy that exhibits early metastatic spread and a high relapse rate. Thus, despite current advanced therapeutic strategies, including chemotherapy and radiation therapy, the 5-year survival rates for SCLC remain between 5 and 10% (4, 5). As SCLC is generally metastasized by the time of diagnosis (6), current diagnostic and prognostic workups for SCLC, such as chest x-rays and computed tomography, are far from efficient in terms of early detection. Therefore, the development of novel diagnostic techniques to identify SCLC is important for the earlier diagnosis of primary or recurring cancers to facilitate more effective treatments and improved prognosis (6). The identification of novel serum biomarkers is a prominent solution for the convenient and easy diagnosis and early detection of cancer, and a combination of markers is expected to enhance sensitivity and specificity.Glycosylation is one of the major post-translational modifications of proteins for cellular function. Approximately 50% of human serum proteins, including secretory and membrane-bound proteins, are suggested to exhibit various N-linked glycosylation patterns (7). Such glycan structures of proteins during carcinogenesis can affect various aspects of the biological behaviors of tumor cells (8–11). In fact, altered glycosylation patterns have long been recognized as hallmarks of cancer progression, in which tumor-specific glycoproteins are actively involved in neoplastic progression and metastasis (12–14). The sensitive detection of such disease-associated glycosylation changes and abnormalities can become a unique landmark to develop diagnostic and prognostic glycoprotein biomarkers.Among the carbohydrate structures on glycoproteins that are altered during carcinogenesis, much interest has been focused on the terminal monosaccharides, fucose and sialic acid (15, 16). Such terminal structures of monosaccharides are known to be involved in biological functions, including cellular recognition, fertilization, and development (17). Fucose is a constituent of the terminal structure of glycan chains and is associated with cancer and inflammation (10). The altered fucosylation of N-linked glycans has been reported in various cancers such as prostate cancer, breast cancer, liver cancer, ovarian cancer, and pancreatic cancer (18). The biological role of fucosylation in cancer is associated with cancer metastasis, tumor immune surveillance, modification of growth factor receptors, and cancer cell interaction with adhesion molecules (19). Carbohydrate antigen 19-9 and α-fetoprotein (AFP)-L3 fraction, which are fucosylated glycoproteins, have been used as tumor markers in the sera of patients with pancreatic and liver cancers, respectively (20). The fucosylated form of AFP (AFP-L3) has demonstrated more robust diagnostic power than AFP itself (21). Therefore, the analysis of specific glycosylated serum glycoproteins represents an important approach for the development of cancer diagnostic biomarkers.Glycoproteomic technologies, such as mass spectrometry-based approaches, have significantly improved biomarker discovery. Thus, in this study, we performed a proteomic screening of fucosylated glycoproteins associated with SCLC. We found that altered fucosylated glycoproteins, specifically the altered fucosylated glycan patterns of PON1, can serve as potential diagnostic and prognostic biomarkers for SCLC.     

Serum NSE, CEA, CT, CA 15-3 levels in human lung cancer

The significance of neuron specific enolase (NSE) was investigated in comparison with other tumor markers (CEA, CT, CA 15-3) used in the diagnosis and treatment monitoring of lung cancer. As previously described, the calcitonin assay proved to have very low sensitivity for small cell lung cancer (SCLC). The serum NSE assay was, however, shown to be a useful diagnostic aid for discrimination between histologically different lung cancers, and therefore this assay may be a valuable tool for treatment monitoring in SCLC patients. CA 15-3, also an unspecific marker, showed similar sensitivity to the NSE assay in SCLC patients, the sensitivity being higher than CEA in non small cell lung cancer (NSCLC).     

Serum biomarkers in interstitial lung diseases

The use of biomarkers in medicine lies in their ability to detect disease and support diagnostic and therapeutic decisions. New research and novel understanding of the molecular basis of the disease reveals an abundance of exciting new biomarkers who present a promise for use in the everyday clinical practice. The past fifteen years have seen the emergence of numerous clinical applications of several new molecules as biologic markers in the research field relevant to interstitial lung diseases (translational research). The scope of this review is to summarize the current state of knowledge about serum biomarkers in interstitial lung diseases and their potential value as prognostic and diagnostic tools and present some of the future perspectives and challenges.     

小细胞肺癌分子标记物研究进展

肺癌仍然是现在最常见的恶性肿瘤之一。小细胞肺癌(Smallcelllungcancer,SCLC)是肺癌中恶性程度最高的一种类型,与吸烟密切相关,其较早发生远处转移和播散导致预后差,目前的主要治疗手段有手术、化学治疗、放射治疗。但其具有初始化放疗敏感,却很快耐受的特点,导致了它总体预后不良,生存期短。如何寻求一种有效的疾病预后、疗效判断标记物,显得尤为重要。本文主要介绍近年来在小细胞肺癌中分子标记物的研究进展,包括神经内分泌的相关蛋白、凋亡蛋白抑制剂(Survivin)、相关酶类及膜蛋白,这些分子标记物与小细胞肺癌疾病的进展、预后密切相关,能够为临床的疾病治疗评估提供潜在可行的方法。但是,这些标记物仍存在特异性不高的问题,最终应用于临床实践,仍需要更多的临床研究。     

Finding biomarkers for non-small cell lung cancer diagnosis and prognosis

Despite of several decades of efforts,lung cancer remains one of most deadly diseases,with a 5-year survival rate approximately 15％ worldwide.In China,the situation is even worse.Although there is no o...     

Protein arrays as tools for serum autoantibody marker discovery in cancer

Protein array technology has begun to play a significant role in the study of protein–protein interactions and in the identification of antigenic targets of serum autoantibodies in a variety of autoimmune disorders. More recently, this technology has been applied to the identification of autoantibody signatures in cancer.The identification of tumour-associated antigens (TAAs) recognised by the patient's immune response represents an exciting approach to identify novel diagnostic cancer biomarkers and may contribute towards a better understanding of the molecular mechanisms involved. Circulating autoantibodies have not only been used to identify TAAs as diagnostic/prognostic markers and potential therapeutic targets, they also represent excellent biomarkers for the early detection of tumours and potential markers for monitoring the efficacy of treatment. Protein array technology offers the ability to screen the humoral immune response in cancer against thousands of proteins in a high throughput technique, thus readily identifying new panels of TAAs. Such an approach should not only aid in improved diagnostics, but has already contributed to the identification of complex autoantibody signatures that may represent disease subgroups, early diagnostics and facilitated the analysis of vaccine trials.     

Biomarkers in molecular medicine: cancer detection and diagnosis

In spite of advances in diagnostics and therapeutics, cancer remains the second leading cause of death in the U.S. Successful cancer treatment depends not only on better therapies but also on improved methods to assess an individual's risk of developing cancer and to detect cancers at early stages when they can be more effectively treated. Current cancer diagnostic imaging methods are labor-intensive and expensive, especially for screening large asymptomatic populations. Effective screening strategies depend on methods that are noninvasive and detect cancers in their early stages of development. There is increasing interest and enthusiasm in molecular markers as tools for cancer detection and prognosis. It is hoped that newly discovered cancer biomarkers and advances in high-throughput technologies would revolutionize cancer therapies by improving cancer risk assessment, early detection, diagnosis, prognosis, and monitoring therapeutic response. These biomarkers will be used either as stand-alone tests or to complement existing imaging methods.     

Proteomics in prostate cancer biomarker discovery

Despite advances in molecular medicine, genomics, proteomics and translational research, prostate cancer remains the second most common cause of cancer-related mortality for men in the Western world. Clearly, early detection, targeted treatment and post-treatment monitoring are vital tools to combat this disease. Tumor markers can be useful for diagnosis and early detection of cancer, assessment of prognosis, prediction of therapeutic effect and treatment monitoring. Such tumor markers include prostate-specific antigen (prostate), cancer antigen (CA)15.3 (breast), CA125 (ovarian), CA19.9 (gastrointestinal) and serum α-fetoprotein (testicular cancer). However, all of these biomarkers lack sensitivity and specificity and, therefore, there is a large drive towards proteomic biomarker discovery. Current research efforts are directed towards discovering biosignatures from biological samples using novel proteomic technologies that provide high-throughput, in-depth analysis and quantification of the proteome. Several of these studies have revealed promising biomarkers for use in diagnosis, assessment of prognosis, and targeting treatment of prostate cancer. This review focuses on prostate cancer proteomic biomarker discovery and its future potential.     

Multi-biomarker pattern for tumor identification and prognosis

In last decades, the basic, clinical, and translational research efforts have been directed to the identification of standard biomarkers associated with the degree of malignancy. There is an increasingly public health concern for earlier detection of cancer development at stages in which successful treatments can be achieved. To meet this urgent clinical demand, early stage cancer biomarkers supported by reliable and robust experimental data that can be readily applicable in the clinical practice, are required. In the current standard protocols, when one or two of the canonical proliferating index biomarkers are analyzed, contradictory results are frequently reached leading to incorrect cancer diagnostic and unsuccessful therapies. Therefore, the identification of other cellular characteristics or signatures present in the tumor cells either alone or in combination with the well-established proliferation markers emerge as an alternative strategy in the improvement of cancer diagnosis and treatment. Because it is well known that several pathways and processes are altered in tumor cells, the concept of "single marker" in cancer results incorrect. Therefore, this review aims to analyze and discuss the proposal that the molecular profile of different genes or proteins in different altered tumor pathways must be established to provide a better global clinical pattern for cancer detection and prognosis.     

The diagnostic efficacy of circulating miRNAs in monitoring the early development of colitis-induced colorectal cancer

Early detection of colorectal cancer and monitoring the progress in colon carcinogenesis stages is essential to reduce mortality. Therefore, there is continuous search for noninvasive biomarkers with high stability and good sensitivity and specificity. miRNAs have attracted attention as promising biomarkers as they are stably expressed in circulation. The aim of our study is to evaluate the aberrant expression of circulating miRNAs during the stepwise progress of colitis-associated colon cancer. This was accomplished through assessing the expression levels of five miRNAs (miR-141, miR-15b, miR-17-3p, miR-21, and miR-29a) in serum and their corresponding tissue samples through the different cycles of colorectal carcinogenesis cascade using the azoxymethane/dextran sulfate sodium murine model. We also compared the diagnostic performance of these selected miRNAs with the conventional tumor biomarkers CEA and CA 19-9. The results of our study revealed that the expression levels of those miRNAs were dynamically changing in accordance with the tumor development state. Moreover, their aberrant expression in serum was statistically correlated with that in tissue. Our data also revealed that serum miR-15b, miR-21, and miR-29a showed the best performance in terms of diagnostic power. Our findings highlight the efficiency of these circulating miRNAs not only for early diagnostics purposes, but also for monitoring progress in the colorectal carcinogenesis process, and therefore encouraging integrating these noninvasive biomarkers into the clinical diagnostic settings beside the traditional diagnostic markers for accurate screening of the early progress of colon carcinogenesis.     

Application of proteomics in non-small-cell lung cancer

Non-small-cell lung cancer (NSCLC) is a heterogeneous disease with diverse pathological features. Clinical proteomics allows the discovery of molecular markers and new therapeutic targets for this most prevalent type of lung cancer. Some of them may be used to detect early lung cancer, while others may serve as predictive markers of resistance to different therapies. Therapeutic targets and prognostic markers in NSCLC have also been discovered. These proteomics biomarkers may help to pair the individual NSCLC patient with the best treatment option. Despite the fact that implementation of these biomarkers in the clinic appears to be scarce, the recently launched Precision Medicine Initiative may encourage their translation into clinical practice.     

胰腺癌相关肿瘤标志物研究进展

胰腺癌起病隐匿,进展快,预后差,发病率约等于死亡率。胰腺癌死亡率高的原因有发病机制不明,缺乏有效的早期诊断和预后的肿瘤标志物,进展期相关治疗效果不理想。近年来在血清标志物、基因标志物、表观遗传学标志物等分子生物技术及生物信息学方面的发展为胰腺癌的诊断,尤其是早期诊断、评估预后和监测早期复发提供了新的途径。本文就近期胰腺癌相关肿瘤标志物的研究进展作一综述。     

Determination of plasma microRNA for early detection of gastric cancer

Gastric cancer is the fourth most prevalent malignancy worldwide and remains the second most common cause of cancer-related death globally. Understanding the molecular structure of gastric carcinogenesis might identify new diagnostic and therapeutic strategies for this disease. Thus, early detection of gastric cancer is a key measure to reduce the mortality and improve the prognosis of gastric cancer. There have recently been several reports that microRNAs (miRNAs) circulate in highly stable, cell-free forms in blood. Because serum and plasma miRNAs are relatively easy to access, circulating miRNAs also have great potential to serve as non-invasive biomarkers. Although a number of miRNAs associated with gastric cancer have been identified, the underlying mechanism of these miRNAs in tumorigenesis and tumor progression remains to be investigated. The purpose of this study is to identify the potential of serum miRNAs as biomarkers for early detection of gastric cancer patients. RNA was isolated using the High Pure miRNA Isolation Kit (Roche) following the manufacturer’s protocol. cDNA and preamplification protocols were obtained from the isolated plasma miRNAs. The BioMark? 96.96 Dynamic Array (Fluidigm Corporation) for real-time qPCR was used to simultaneously quantite the expression of 740 miRNAs. All statistical analyses were performed using the Biogazelle’s qbase PLUS 2.0 software. In this study, among 740 miRNAs that we analyzed only miR-195-5p was significantly (p < 0.05, fold changes = 13, 3) down-regulated in gastric cancer patients compared with control. We demonstrated that miR-195-5p is a novel tumor suppressor miRNA and may contribute to gastric carcinogenesis. The miRNA expression profile described in this study should contribute to future studies on the role of miRNAs in gastric cancer.