Profiling Tumor-Associated Antibodies for Early Detection of Non-small Cell Lung Cancer:

Biomarkers and molecular testing for early detection, diagnosis, and therapeutic prediction of lung cancer

The search for biomarkers in the management of lung cancer involves the use of multiple platforms to examine changes in gene, protein, and microRNA expression. Multiple studies have been published in an attempt to describe early detection, diagnostic, prognostic, and predictive biomarkers using chiefly tissues and blood elements. Studies are characterized by a lack of commonality of specific biomarkers, and a lack of validated, clinically useful markers. The future of biomarker discovery as a means of tailoring therapy for patients with lung cancer will involve next-generation sequencing along with collaborative efforts to integrate and validate candidate markers.

A study of circulating anti-CD25 antibodies in non-small cell lung cancer

PURPOSE

Tumors can trigger specific immune response to tumor-associated antigens but the precise mechanism remains unclear. Since regulatory T-lymphocytes (Treg) play a crucial role in controlling autoimmune responses, the present work was undertaken to test whether dysfunction of Treg cells could be involved in developing autoimmunity in patients with lung cancer.

METHODS

In this study, we developed an in-house enzyme-linked immunosorbent assay to test circulating anti-CD25 autoantibodies among 272 patients with non-small cell lung cancer (NSCLC) and 226 control subjects matched in age, gender and smoking history.

RESULTS

Mann-Whitney U test showed that the anti-CD25 IgG level was significantly higher in patients with NSCLC than control subjects (Z = -7.48, P < 0.001) while the anti-CD25 IgA level was not significantly changed in the patient group as compared with the control group (Z = -1.34, P = 0.181). Spearman correlation analysis failed to reveal a significant correlation between the levels of anti-CD25 IgG and IgA either in patients with NSCLC (r = -0.034, P = 0.578) or in control subjects (r = 0.055, P = 0.429). ROC analysis showed an AUC of 0.70 for anti-CD25 IgG, in which NSCLC at stage III had the highest AUC (0.75). The sensitivity against a specificity of >90 % was 35.0 % for anti-CD25 IgG assay with an inter-assay deviation of 9.4 %, and 4.0 % for anti-CD25 IgA assay with an inter-assay deviation of 13.0 %.

CONCLUSIONS

Circulating anti-CD25 IgG antibody may be a useful biomarker for prognosis of lung cancer.

Early detection of cancer in the general population: a blinded case-control study of p53 autoantibodies in colorectal cancer

Background:

Recent reports from cancer screening trials in high-risk populations suggest that autoantibodies can be detected before clinical diagnosis. However, there is minimal data on the role of autoantibody signatures in cancer screening in the general population.

Methods:

Informative p53 peptides were identified in sera from patients with colorectal cancer using an autoantibody microarray with 15-mer overlapping peptides covering the complete p53 sequence. The selected peptides were evaluated in a blinded case–control study using stored serum from the multimodal arm of the United Kingdom Collaborative Trial of Ovarian Cancer Screening where women gave annual blood samples. Cases were postmenopausal women who developed colorectal cancer following recruitment, with 2 or more serum samples preceding diagnosis. Controls were age-matched women with no history of cancer.

Results:

The 50 640 women randomised to the multimodal group were followed up for a median of 6.8 (inter-quartile range 5.9–8.4) years. Colorectal cancer notification was received in 101 women with serial samples of whom 97 (297 samples) had given consent for secondary studies. They were matched 1 : 1 with 97 controls (296 serial samples). The four most informative peptides identified 25.8% of colorectal cancer patients with a specificity of 95%. The median lead time was 1.4 (range 0.12–3.8) years before clinical diagnosis.

Conclusion:

Our findings suggest that in the general population, autoantibody signatures are detectable during preclinical disease and may be of value in cancer screening. In colorectal cancer screening in particular, where the current need is to improve compliance, it suggests that p53 autoantibodies may contribute towards risk stratification.

The current status of cancer biomarker research using tumour-associated antigens for minimal invasive and early cancer diagnostics

Tumour-associated antigens (TAA) can be detected prior to clinical diagnosis and thus would be ideal biomarkers for early detection of cancer using only a few microliters of a patient's serum. In this article we provide a summary of TAA screening and serum-profiling conducted for breast, prostate, lung and colon cancers. Different methodological approaches, including SEREX, SERPA, and phage display for TAA identification and TAA panels are summarised, and a revision of array based techniques is provided. The most promising studies performed on these cancers (performed with 80-400 serum samples, including controls) obtained sensitivities in a range of 44-95% and specificities of 80-100%. From the various studies reviewed, only one performed cross validation (AUC=0.71) in a prostate cancer study. Thus, albeit receiver operation characteristics are very promising, cross validation of most studies is still missing. Additionally, the concerted action of research groups for standardization of serum-TAA testing and cross validation is required. Along with today's technological options, the chances of establishing TAA biomarkers are now higher than ever before. This may also be true for confirmation and validation of already existing data, which is a prerequisite for implementation of TAA biomarkers into clinical diagnostics. This article is part of a Special Issue entitled: Integrated omics.

Tumor-associated autoantibody signature for the early detection of gastric cancer

Autoantibodies against tumor-associated antigens are very attractive biomarkers for the development of noninvasive serological tests for the early detection of cancer because of their specificity and stability in the sera. In our study, we applied T7 phage display-based serological analysis of recombinant cDNA expression libraries technique to identify a representative set of antigens eliciting humoral responses in patients with gastric cancer (GC), produced phage-antigen microarrays and exploited them for the survey of autoantibody repertoire in patients with GC and inflammatory diseases. We developed procedures for data normalization and cutoff determination to define sero-positive signals and ranked them by the signal intensity and frequency of reactivity. To identify autoantibodies with the highest diagnostic value, a 1,150-feature microarray was tested with sera from 100 patients with GC and 100 cancer-free controls, and then the top-ranked 86 antigens were used for the production of focused array that was tested with an independent validation set comprising serum samples from 235 patients with GC, 154 patients with peptic ulcer and gastritis and 213 healthy controls. The receiver operating characteristic curve analysis showed that 45-autoantibody signature could discriminate GC and healthy controls with area under the curve (AUC) of 0.79 (59% sensitivity and 90% specificity), GC and peptic ulcer with AUC of 0.76 and GC and gastritis with AUC of 0.64. Moreover, it could detect early GC with equal sensitivity than advanced GC. Interestingly, the autoantibody production did not correlate with histological type, H. pylori status, grade, localization and size of the primary tumor, whereas it appeared to be associated with the metastatic disease.

Are circulating autoantibodies to ABCC3 transporter a potential biomarker for lung cancer?

PURPOSE

The present study was undertaken to test circulating autoantibody to ATP-binding cassette C3 (ABCC3) transporter in order to confirm whether anti-ABCC3 antibody could serve as a biomarker for early diagnosis of lung cancer.

METHODS

This study recruited 275 patients (178 males and 97 females) with non-small cell lung cancer (either squamous carcinoma or adenocarcinoma) and 226 control subjects (134 males and 92 females) well matched in age and smoking history. Anti-ABCC3 IgA and IgG were determined using an enzyme-linked immunosorbent assay (ELISA) approach that was developed in house with the human leukocyte antigen class II (HLA-II) restricted antigens.

RESULTS

Mann-Whitney U test showed that the IgG antibody level was significantly higher in female patients with adenocarcinoma than female controls (Z = -4.34, P < 0.001) and that the IgA antibody level was significantly higher in male patients with squamous carcinoma than male controls (Z = -3.12, P = 0.002). Pearson's Chi-square (χ(2)) test showed that female patients with adenocarcinoma had a significantly higher positive rate for IgG autoantibody than female controls (χ ( 2 ) = 8.73, P = 0.003). The ELISA sensitivity against a specificity of >95 % was 18.1 % for IgG assay in female patients and 18.0 % for IgA assay in male patients. The inter-assay deviation was 10.6 % for IgG assay and 14.5 % for IgA assay.

CONCLUSIONS

Circulating autoantibodies to ABCC3 transporter may be a potential biomarker that can be added to a panel of existing biomarkers for early diagnosis and prognosis of lung cancer although the gender differences should be taken into account.

The state of molecular biomarkers for the early detection of lung cancer

Using biomarkers to select the most at-risk population, to detect the disease while measurable and yet not clinically apparent has been the goal of many investigations. Recent advances in molecular strategies and analytic platforms, including genomics, epigenomics, proteomics, and metabolomics, have identified increasing numbers of potential biomarkers in the blood, urine, exhaled breath condensate, bronchial specimens, saliva, and sputum, but none have yet moved to the clinical setting. Therefore, there is a recognized gap between the promise and the product delivery in the cancer biomarker field. In this review, we define clinical contexts where risk and diagnostic biomarkers may have use in the management of lung cancer, identify the most relevant candidate biomarkers of early detection, provide their state of development, and finally discuss critical aspects of study design in molecular biomarkers for early detection of lung cancer.

Detection methodology based on target molecule-induced sequence-specific binding to a single-stranded oligonucleotide

We have recently developed a mix-and-read format homogeneous antigen peptide based assay for detection of the antibodies (Tian, L.; Heyduk, T. Anal. Chem. 2009, 81, 5218-5225) that employed for target detection a simple biophysical mechanism of target antibody induced annealing between two complementary oligonucleotides attached to the antigen peptide. In this work, we propose and experimentally validate an alternative variant of this assay format in which target antibody binding to antigen peptide-oligonucleotide conjugate produces a complex with high sequence-specific binding affinity to a single-stranded capture oligonucleotide. This new assay format can be used for preparing various solid-surface based assays by immobilizing the capture oligonucleotide. This assay design is not limited to antibody detection. We demonstrate that it can also be employed for detecting proteins or pathogenic bacteria using oligonucleotide-labeled antibodies as target recognition elements. Preparation of these solid-surface based assays is simplified because all interactions with the solid surfaces are mediated by well-understood oligonucleotide-oligonucleotide interactions and because of the relative ease of immobilizing oligonucleotides on various solid surfaces. These unique aspects of the assay design also allow microarray-style multiplexing that could be most useful for multiplexed antibody profiling for diagnosis and analysis of cancer, autoimmune, and infectious diseases.

Antibody profiling with protein antigen microarrays in early stage cancer

INTRODUCTION

Proteins not present in normal cells, that is, cancer cells, may elicit a host immune response that leads to the generation of antibodies that might react with these tumor-associated proteins. In recent years, a growing number of reports have showed that autoantibody profiling may provide an alternative approach for the detection of cancer. However, most studies of antigen-autoantibody reactivity have relied on recombinant proteins. Recombinant proteins lack the proper post-translational modifications present in native proteins. Because of this limitation, native or natural protein antigen microarrays are gaining popularity for profiling antibody responses.

AREAS COVERED

i) To illustrate some examples of autoantibodies as signatures for early stage cancer; ii) to briefly outline the various protein antigen microarray platforms; iii) to illustrate the use of native or natural protein microarrays in the discovery of potential biomarkers and iv) to discuss the advantages of native protein antigen microarrays over other approaches.

EXPERT OPINION

The nature of protein microarray platforms is conducive to multiplexing, which amplifies the potential for uncovering effective biomarkers for many significant diseases. However, the major challenge will be in integrating microarray platforms into multiplexed clinical diagnostic tools, as the main drawback is the reproducibility and coefficient of variation of the results from array to array, and the transportability of the array platform to a more automatable platform.

Serologic laboratory findings in malignancy

Autoantibodies are extremely promising diagnostic and prognostic biomarkers of cancer, and have the potential to promote early diagnosis and to make a large impact by improving patient outcome and decreasing mortality. Moreover, autoantibodies may be useful reagents in the identification of subjects at risk for cancer, bearing premalignant tissue changes. Great efforts are being made in many laboratories to validate diagnostic panels of autoantibodies with high sensitivity and specificity that could be useful in a clinical setting. It is likely that prospective studies of sufficiently large cohorts of patients and controls using high-throughput technology may allow the identification of biomarkers with diagnostic significance, and perhaps of discrete antigen phenotypes with clinical significance. The identification of TAAs may also be essential for the development of anticancer vaccines, because autoantibodies found in cancer sera target molecules involved in signal transduction, cell-cycle regulation, cell proliferation, and apoptosis, playing important roles in carcinogenesis. On this basis, molecular studies of antigenantibody systems in cancer promise to yield valuable information on the carcinogenic process. TAAs identified by serum antibodies in cancer sera can be natural immunogenic molecules, useful as targets for cancer immunotherapy. An important problem encountered in the practice of medicine is the identification of healthy individuals in the general population who unknowingly are at high risk of developing cancer. For the rheumatologist, a related problem is the identification of those patients with rheumatic diseases who are at high risk for developing a malignant process. These problems encountered in the fields of cancer and the rheumatic diseases can in the future be helped by new diagnostic instruments based on antibodies. The need for promoting the early diagnosis of cancer is a recognized major public health problem in need of significant research support for the validation of multiple promising but inconclusive studies, with the intention of producing diagnostic panels of autoantibodies in various types of cancers. Cancer developing in patients with rheumatic diseases is also an important problem requiring prospective longterm follow-up studies of patients with rheumatic diseases, particularly because some of the new biologic therapies seem to increase the cancer risk. It is possible that a panel of autoantibodies common to patients with cancer and the rheumatic diseases may prove to be of value in the identification of those patients with ADs at high risk for neoplasms.

Autoantibody signatures: progress and perspectives for early cancer detection

Becoming invasive is a crucial step in cancer development, and the early spread of tumour cells is usually undetected by current imaging technologies. In patients with cancer and no signs of overt metastases, sensitive methods have been developed to identify circulating autoantibodies and their antigen counterparts in several cancers. These technologies are often based on proteomic approaches, and recent advances in protein and antibody microarrays have greatly facilitated the discovery of new antibody biomarkers in sera from cancer patients. Interestingly, in a clinical application setting, combinations of multiple autoantibody reactivities into panel assays have recently been proposed as relevant screening tests and validated in several independent trials. In addition, autoantibody signatures seem to be particularly relevant for early detection of cancer in high-risk cancer patients. In this review, we highlight the concept that immunogenic epitopes associated with the humoural response and key pathogenic pathways elicit serum autoantibodies that can be considered as relevant cancer biomarkers. We outline the proteomic strategies employed to identify and validate their use in clinical practice for cancer screening and diagnosis. We particularly emphasize the clinical utility of autoantibody signatures in several cancers. Finally, we discuss the challenges remaining for clinical validation.

Mass spectrometry analyses of κ and λ fractions result in increased number of complementarity-determining region identifications

Sera from lung cancer patients contain antibodies against tumor-associated antigens. Specific amino acid sequences of the complementarity-determining regions (CDRs) in the antigen-binding fragment (Fab) of these antibodies have potential as lung cancer biomarkers. Detection and identification of CDRs by mass spectrometry can significantly be improved by reduction of the complexity of the immunoglobulin molecule. Our aim was to molecular dissect IgG into κ and λ fragments to reduce the complexity and thereby identify substantially more CDRs than by just total Fab isolation. We purified Fab, Fab-κ, Fab-λ, κ and λ light chains from serum from 10 stage I lung adenocarcinoma patients and 10 matched controls from the current and former smokers. After purification, the immunoglobulin fragments were enzymatically digested and measured by high-resolution mass spectrometry. Finally, we compared the number of CDRs identified in these immunoglobulin fragments with that in the Fab fragments. Twice as many CDRs were identified when Fab-κ, Fab-λ, κ and λ (3330) were combined than in the Fab fraction (1663) alone. The number of CDRs and κ:λ ratio was statistically similar in both cases and controls. Molecular dissection of IgG identifies significantly more CDRs, which increases the likelihood of finding lung cancer-related CDR sequences.

EarlyCDT-Lung: an immunobiomarker test as an aid to early detection of lung cancer

Recent publications have reported the technical and clinical validation of EarlyCDT-Lung, an autoantibody test which detected elevated autoantibodies in 40% of lung cancers at diagnosis. This manuscript reports the results of EarlyCDT-Lung run on four new (postvalidation) data sets. The following four cohorts of patients (n = 574) with newly diagnosed lung cancer were identified: group 1 (n = 122), 100% small cell lung cancer (SCLC); group 2 (n = 249), 97% non-small cell lung cancer (NSCLC); group 3 (n = 122), 100% NSCLC; group 4 (n = 81), 62% NSCLC. Serum samples were obtained after diagnosis, prior to any anticancer treatment. Autoantibody levels were measured against a panel of six tumor-related antigens (p53, NY-ESO-1, CAGE, GBU4-5, Annexin 1, and SOX2) in the EarlyCDT-Lung panel and previously established cutoffs applied. In groups 2, 3, and 4, patients were individually matched by gender, age, and smoking history to a control individual with no history of malignant disease. Assay sensitivity was tested in relation to cancer type and stage, and in the matched normals to demographic variables. The autoantibody panel showed sensitivity/specificity of 57%/n.d (not done) for SCLC in group 1, 34%/87% for NSCLC in group 2, 31% and 84% for NSCLC in group 3, and 35%/89% for NSCLC and 43%/89% for SCLC in group 4. There was no significant difference in positivity of EarlyCDT-Lung and different lung cancer stages. These studies confirm the value of an autoantibody assay, EarlyCDT-Lung, as an aid to detecting lung cancer in patients at high risk of the disease.

Non-small-cell lung cancer

In the decade since the last Lancet Seminar on lung cancer there have been advances in many aspects of the classification, diagnosis, and treatment of non-small-cell lung cancer (NSCLC). An international panel of experts has been brought together to focus on changes in the epidemiology and pathological classification of NSCLC, the role of CT screening and other techniques that could allow earlier diagnosis and more effective treatment of the disease, and the recently introduced seventh edition of the TNM classification and its relation to other prognostic factors such as biological markers. We also describe advances in treatment that have seen the introduction of a new generation of chemotherapy agents, a proven advantage to adjuvant chemotherapy after complete resection for specific stage groups, new techniques for the planning and administration of radiotherapy, and new surgical approaches to assess and reduce the risks of surgical treatment.

Multicenter study identified molecular blood-born protein signatures for Wilms Tumor

Wilms Tumor (WT) is the most common renal childhood tumor. Recently, we reported a cDNA microarray expression pattern that varied between WTs with different risk histology. Since the Societé Internationale d'Oncologie Pédiatrique (SIOP) in Europe initiates treatment without a histological confirmation, it is important to identify blood-born markers that indicate WT development. In a multicenter study, we established an autoantibody signature by using an array with 1,827 recombinant E. coli clones. This array was screened with sera of patients with WT recruited by SIOP or the Children's Oncology Group (COG). We report an extended number of antigens that are reactive with autoantibodies present in sera from patients with WT. We established an autoantibody signature that separates untreated patients with WT recruited in SIOP from non-WT controls with a specificity of 0.83 and a sensitivity of 0.82 at standard deviations of 0.02 and 0.04, respectively. Likewise, patients recruited in the COG in the United States were separated from the controls with an accuracy of 0.83 at a standard deviation of 0.02. Proteins that were most significant include zinc finger proteins (e.g., ZFP 346), ribosomal proteins and the protein fascin that has been associated with various types of cancer including renal cell carcinoma. Our study provides first evidence for autoantibody signatures for WTs and suggests that these may be most informative before chemotherapy. We present the first multicenter study of autoantibody signatures in patients with WT. We established an autoantibody signature that separates patients with WT from controls.

Discovery of lung cancer biomarkers by profiling the plasma proteome with monoclonal antibody libraries

A challenge in the treatment of lung cancer is the lack of early diagnostics. Here, we describe the application of monoclonal antibody proteomics for discovery of a panel of biomarkers for early detection (stage I) of non-small cell lung cancer (NSCLC). We produced large monoclonal antibody libraries directed against the natural form of protein antigens present in the plasma of NSCLC patients. Plasma biomarkers associated with the presence of lung cancer were detected via high throughput ELISA. Differential profiling of plasma proteomes of four clinical cohorts, totaling 301 patients with lung cancer and 235 healthy controls, identified 13 lung cancer-associated (p < 0.05) monoclonal antibodies. The monoclonal antibodies recognize five different cognate proteins identified using immunoprecipitation followed by mass spectrometry. Four of the five antigens were present in non-small cell lung cancer cells in situ. The approach is capable of generating independent antibodies against different epitopes of the same proteins, allowing fast translation to multiplexed sandwich assays. Based on these results, we have verified in two independent clinical collections a panel of five biomarkers for classifying patient disease status with a diagnostics performance of 77% sensitivity and 87% specificity. Combining CYFRA, an established cancer marker, with the panel resulted in a performance of 83% sensitivity at 95% specificity for stage I NSCLC.

Autoantibodies against p53 are associated with chromosome 17p deletions in chronic lymphocytic leukemia

Autoantibodies against p53 have been observed in many cancers, often linked with abnormalities in the TP53 gene. Since p53 mutations and deletions at chromosome 17p are known to occur in CLL, we measured anti-p53 autoantibodies by ELISA in plasma samples from patients with normal cytogenetics as well as those with 13q, 11q, and 17p deletions as well as trisomy 12. Anti-p53 autoantibodies were detected in over half of the patients with a 17p deletion but in very few of the others. There was no correlation between the levels of anti-p53 antibodies and the percentage of cells with 17p abnormalities. The levels of the anti-p53 autoantibodies remained stable for most patients with serial samples. Increased levels of antibodies that bound to two peptide fragments of p53 were also seen in patients with 17p deletions. At least on case with high levels of anti-p53 autoantibodies had a heterozygotic mutation known to result in a dominant negative phenotype, suggesting that aberrant expression of p53 may contribute to the development of autoantibodies and suggests that these autoantibodies may reflect biological features relevant to prognosis.

Screening and early detection of lung cancer

Lung cancer with an estimated 342,000 deaths in 2008 (20% of total) is the most common cause of death from cancer, followed by colorectal cancer (12%), breast cancer (8%), and stomach cancer (7%) in Europe. In former smokers, the absolute lung cancer risk remains higher than in never-smokers; these data therefore call for effective secondary preventive measures for lung cancer in addition to smoking cessation programs. This review presents and discusses the most recent advances in the early detection and screening of lung cancer.An overview of randomized controlled computerized tomography-screening trials is given, and the role of bronchoscopy and new techniques is discussed. Finally, the approach of (noninvasive) biomarker testing in the blood, exhaled breath, sputum, and bronchoscopic specimen is reviewed.

Autoantibodies to aberrantly glycosylated MUC1 in early stage breast cancer are associated with a better prognosis

Introduction

Detection of serum biomarkers for early diagnosis of breast cancer remains an important goal. Changes in the structure of O-linked glycans occur in all breast cancers resulting in the expression of glycoproteins that are antigenically distinct. Indeed, the serum assay widely used for monitoring disease progression in breast cancer (CA15.3), detects a glycoprotein (MUC1), but elevated levels of the antigen cannot be detected in early stage patients. However, since the immune system acts to amplify the antigenic signal, antibodies can be detected in sera long before the antigen. We have exploited the change in O-glycosylation to measure autoantibody responses to cancer-associated glycoforms of MUC1 in sera from early stage breast cancer patients.

Methods

We used a microarray platform of 60mer MUC1 glycopeptides, to confirm the presence of autoantibodies to cancer associated glycoforms of MUC1 in a proportion of early breast cancer patients (54/198). Five positive sera were selected for detailed definition of the reactive epitopes using on chip glycosylation technology and a panel of glycopeptides based on a single MUC1 tandem repeat carrying specific glycans at specific sites. Based on these results, larger amounts of an extended repertoire of defined MUC1 glycopeptides were synthesised, printed on microarrays, and screened with sera from a large cohort of breast cancer patients (n = 395), patients with benign breast disease (n = 108) and healthy controls (n = 99). All sera were collected in the 1970s and 1980s and complete clinical follow-up of breast cancer patients is available.

Results

The presence and level of autoantibodies was significantly higher in the sera from cancer patients compared with the controls, and a highly significant correlation with age was observed. High levels of a subset of autoantibodies to the core3MUC1 (GlcNAcβ1-3GalNAc-MUC1) and STnMUC1 (NeuAcα2,6GalNAc-MUC1) glycoforms were significantly associated with reduced incidence and increased time to metastasis.

Conclusions

Autoantibodies to specific cancer associated glycoforms of MUC1 are found more frequently and at higher levels in early stage breast cancer patients than in women with benign breast disease or healthy women. Association of strong antibody response with reduced rate and delay in metastases suggests that autoantibodies can affect disease progression.

Immunobiomarkers in small cell lung cancer: potential early cancer signals

PURPOSE

We investigated the presence of autoantibodies as immunobiomarkers to a panel of tumor-associated antigens in a group of individuals with small cell lung cancer (SCLC), a disease group that has a poor overall cancer prognosis and therefore may benefit most from early diagnosis.

EXPERIMENTAL DESIGN

Sera from 243 patients with confirmed SCLC and normal controls matched for age, sex, and smoking history were analyzed for the presence of these early immunobiomarkers (i.e., autoantibodies to p53, CAGE, NY-ESO-1, GBU4-5, Annexin I, SOX2, and Hu-D) by ELISA.

RESULTS

Autoantibodies were seen to at least 1 of 6 antigens in 55% of all the SCLC patients' sera tested, with a specificity of 90% compared with controls. Using a higher assay cutoff to achieve a specificity of 99%, autoantibodies were still detectable in 42% of SCLC patients (receiver operator characteristic area under the curve = 0.76). There was no significant difference in sensitivity when analyzed by stage of the cancer or by patient age or gender. The frequency of autoantibodies to individual antigens varied, ranging from 4% for GBU4-5 to 35% for SOX2. Levels of Annexin I autoantibodies were not elevated in patients with SCLC. Antibodies were also detected in 4 separate patients whose sera were taken up to 3 months before tumor diagnosis.

CONCLUSION

The presence of an autoantibody to one or more cancer-associated antigens may provide an important addition to the armamentarium available to the clinician to aid early detection of SCLC in high-risk individuals.

Enhancement of a multianalyte serum biomarker panel to identify lymph node metastases in non-small cell lung cancer with circulating autoantibody biomarkers

We recently reported the development of a multianalyte serum algorithm to identify nodal status in non-small cell lung cancer (NSCLC) patients facing an anatomic resection with curative intent. This study aims to enhance the overall performance characteristics of this test by adding autoantibody biomarkers identified through immunoproteomic discovery. More specifically, we used sera from 20 NSCLC patients to probe 2-D immunoblots of HCC827 lysates for tumor-associated autoantigens. Relevant differences in immunoreactivity associated with pathological nodal status were then identified via tandem mass spectrometry. Identified autoantigens were then developed into Luminex immunobead assays alongside a series of autoantigen targets relevant to early-disease detection. These assays were then used to measure circulating autoantibody levels in the identical cohort of NSCLC patients used in our original study. This strategy identified 11 autoantigens found primarily in patients with disease progression to the locoregional lymph nodes. Custom Luminex-based "direct-capture" assays (25 total; including autoantibody targets relevant to early-disease detection) were assembled to measure autoantibody levels in sera from 107 NSCLC patients. Multivariate classification algorithms were then used to identify the optimal combination of biomarkers when considered collectively with our original 6-analyte serum panel. The new algorithm resulting from this analysis consists of TNF-α, TNF-RI, MIP-1α and autoantibodies against Ubiquilin-1, hydroxysteroid-(17-β)-dehydrogenase, and triosephosphate isomerase. The inclusion of autoantibody biomarkers provided a dramatic improvement in the overall test performance characteristics, relative to the original test panel, including an 11% improvement in the classification efficiency.

Lung cancer-associated auto-antibodies measured using seven amino acid peptides in a diagnostic blood test for lung cancer

Autoantibody profiling is a developing approach that incorporates immune recognition of myriad aberrant cancer proteins into a single diagnostic assay. We have previously described methodology to screen T7-phage NSCLC-cDNA libraries for phage-expressed proteins recognized by NSCLC-associated antibodies, and developed a multiplex assay that has excellent ability to discriminate NSCLC from control samples. This follow-up report describes the development and testing of a diagnostic autoantibody assay that uses seven amino-acid peptides as capture proteins. A random-peptide M13-phage library was screened for proteins recognized by cancer-associated antibodies. One hundred twenty-one NSCLC case and control samples were divided into two groups for training and validation, or alternately, evaluated sequentially in a leave-one-out analysis. Candidate antibody-markers were ranked by statistical discrimination between cases and controls. Receiver-Operating-Characteristic (ROC-AUC) suggested the predictive potential of various marker combinations. A five-marker combination (AUC = 0.982) afforded 90% sensitivity and 73% specificity in a training-and-testing strategy. Leave-one-out validation provided similar class prediction. Data confirm the potential of antibody profiling to provide high levels of cancer prediction. Random peptide libraries offer a universal source of capture proteins for antibody profiling that obviates the need for tumor-specific library construction and abrogates inherent problems with tumor heterogeneity during biomarker discovery.

Clinical validation of an autoantibody test for lung cancer

Background: Autoantibodies may be present in a variety of underlying cancers several years before tumours can be detected and testing for their presence may allow earlier diagnosis. We report the clinical validation of an autoantibody panel in newly diagnosed patients with lung cancer (LC).

Patients and methods: Three cohorts of patients with newly diagnosed LC were identified: group 1 (n = 145), group 2 (n = 241) and group 3 (n = 269). Patients were individually matched by gender, age and smoking history to a control individual with no history of malignant disease. Serum samples were obtained after diagnosis but before any anticancer treatment. Autoantibody levels were measured against a panel of six tumour-related antigens (p53, NY-ESO-1, CAGE, GBU4-5, Annexin 1 and SOX2). Assay sensitivity was tested in relation to demographic variables and cancer type/stage.

Results: The autoantibody panel demonstrated a sensitivity/specificity of 36%/91%, 39%/89% and 37%/90% in groups 1, 2 and 3, respectively, with good reproducibility. There was no significant difference between different LC stages, indicating that the antigens included covered the different types of LC well.

Conclusion: This assay confirms the value of an autoantibody panel as a diagnostic tool and offers a potential system for monitoring patients at high risk of LC.

Implications of cancer-associated systemic inflammation for biomarker studies

Highly sensitive molecular technologies provide new capacities for cancer biomarker research, but with sensitivity improvements marker specificity is significantly decreased, and too many false-positive results should disqualify the measurement from clinical use. Hence, of the thousands of potential cancer biomarkers only a few have found their way to clinical application. Differentiating false-positive results from true-positive (cancer-specific) results can indeed be difficult, if validation of a marker is performed against inadequate controls. We present examples of accumulating evidence that not only local but also systemic inflammatory reactions are implicated in cancer development and progression and interfere with the molecular image of cancer disease. We analyze several modern strategies of tumor marker discovery, namely, proteomics, metabonomics, studies on circulating tumor cells and circulating free nucleic acids, or their methylation degree, and provide examples of scarce, methodologically correct biomarker studies as opposed to numerous methodologically flawed biomarker studies, that examine cancer patients' samples against those of healthy, inflammation-free persons and present many inflammation-related biomarker alterations in cancer patients as cancer-specific. Inflammation as a cancer-associated condition should always be considered in cancer biomarker studies, and biomarkers should be validated against their expression in inflammatory conditions.

Development of a multiplexed tumor-associated autoantibody-based blood test for the detection of non-small cell lung cancer

PURPOSE

Non-small cell lung cancer (NSCLC) has an overall 5-year survival of <15%; however, the 5-year survival for stage I disease is over 50%. Unfortunately, 75% of NSCLC is diagnosed at an advanced stage not amenable to surgery. A convenient serum assay capable of unambiguously identifying patients with NSCLC may provide an ideal diagnostic measure to complement computed tomography-based screening protocols.

EXPERIMENTAL DESIGN

Standard immunoproteomic method was used to assess differences in circulating autoantibodies among lung adenocarcinoma patients relative to cancer-free controls. Candidate autoantibodies identified by these discovery phase studies were translated into Luminex-based "direct-capture" immunobead assays along with 10 autoantigens with previously reported diagnostic value. These assays were then used to evaluate a second patient cohort composed of four discrete populations, including: 117 NSCLC (81 T(1-2)N(0)M(0) and 36 T(1-2)N(1-2)M(0)), 30 chronic obstructive pulmonary disorder (COPD)/asthma, 13 nonmalignant lung nodule, and 31 "normal" controls. Multivariate statistical methods were then used to identify the optimal combination of biomarkers for classifying patient disease status and develop a convenient algorithm for this purpose.

RESULTS

Our immunoproteomic-based biomarker discovery efforts yielded 16 autoantibodies differentially expressed in NSCLC versus control serum. Thirteen of the 25 analytes tested showed statistical significance (Mann-Whitney P < 0.05 and a receiver operator characteristic "area under the curve" over 0.65) when evaluated against a second patient cohort. Multivariate statistical analyses identified a six-biomarker panel with only a 7% misclassification rate.

CONCLUSIONS

We developed a six-autoantibody algorithm for detecting cases of NSCLC among several high-risk populations. Population-based validation studies are now required to assign the true value of this tool for identifying early-stage NSCLC.

Development of autoantibody signatures as novel diagnostic biomarkers of non-small cell lung cancer

PURPOSE

To select autoantibody signatures as noninvasive biomarkers of non-small cell lung cancer (NSCLC).

EXPERIMENTAL DESIGN

A phage cDNA expression library was constructed with fresh samples from 30 lung cancer patients and biopanned using serum pools of 10 NSCLC patients and 10 healthy controls. A six-phage peptide detector was discovered by two-step immunoscreenings and was validated in an independent set of 90 NSCLC patients and 90 matched healthy controls, 30 NSCLC patients with chemotherapy, and 12 chronic obstructive pulmonary disease (COPD) patients. The expression of a peptide target was validated by using immunohistochemistry. Factors affecting NSCLC-related death were evaluated by Cox regression analysis.

RESULTS

Six phage peptide clones showing higher seroreactivity than others in 30 NSCLC patients were selected for diagnostic validation. The six-phage peptide detector was able to discriminate between NSCLC patients and healthy controls with a sensitivity and specificity of >92%, and had similar validity for indicating NSCLC at early stage. The seroreactivity of the six phage peptides was significantly higher in the NSCLC patients than in those with chemotherapy and the COPD patients, respectively. Of the six phage peptides, one encoded a peptide showing 100% homology to olfactomedin 1. Expression of olfactomedin 1 protein was significantly higher in lung adenocarcinoma than in lung cancer of other histologic types and normal lung tissues. The autoantibody signature was not associated with the prognosis of the NSCLC patients.

CONCLUSIONS

The six-phage peptide detector stands out as promising diagnostic biomarkers for NSCLC, unlikely for NSCLC relapse after chemotherapy. Olfactomedin 1 may be a novel target of lung adenocarcinoma.

Autoimmunity to SOX2, clinical phenotype and survival in patients with small-cell lung cancer

OBJECTIVE

Autoantibodies to SOXB1 antigens are commonly found in patients with small-cell lung cancer (SCLC). It has not been established whether the presence of circulating SOX antibodies is associated with a specific paraneoplastic clinical phenotype, or if a tumour immune response to SOX antigens can affect prognosis in patients with SCLC in relation to other established prognostic factors.

METHODS

Using recombinant SOX2 in an ELISA, we analysed sera in a prospective study from 212 unselected SCLC patients, which included 35 patients with neurological paraneoplastic disorders, or other well characterised onconeural antibodies.

RESULTS

Overall, SOX2 antibodies were detected in 70 SCLC patients, with a sensitivity of 33% (95% CI 27-40%) and specificity of 97% (95% CI 94-99%) compared to controls matched for age, gender and smoking history. No single clinical phenotype was seen in relation to the presence of SOX2 antibodies in isolation. Multivariate analysis showed that the presence of SOX2 antibodies in SCLC patients without evidence of neurological paraneoplastic disorders or onconeural antibodies did not have a significant effect on survival when known prognostic factors were accounted for.

CONCLUSIONS

SOX2 antibodies are very specific markers for SCLC compared to matched non-tumour controls, but their presence does not seem to alter prognosis in this tumour type.

New biomarkers for lung cancer

IMPORTANCE OF THE FIELD

Despite many efforts to improve early detection, lung cancer remains the leading cause of cancer deaths. Stage is the main determinant of prognosis and the basis for deciding treatment options. Screening tests for lung cancer have not been successful so far.

AREAS COVERED IN THE REVIEW

The article reviews the available literature related to biomarkers in use at present and those that could be used for early diagnosis, staging, prognosis, response to therapy and prediction of recurrence. The single biomarkers are analysed, divided according to the technological methods used and the locations of sampling.

WHAT THE READER WILL GAIN

The reader will gain knowledge on biomarkers in use and those now under study. The reader will also gain insights into the difficulties pertaining to the development of biomarkers, results reproducibility and clinical application.

TAKE HOME MESSAGE

Although some markers seem to be promising, at present there is no consensus on the proven value of their clinical use in lung cancer. The future lies probably in a panel of biomarkers instead of individual assays, or in predictive models derived from the integration of clinical variables and gene expression profiles.

Technical validation of an autoantibody test for lung cancer

Background: Publications on autoantibodies to tumour-associated antigens (TAAs) have failed to show either calibration or reproducibility data. The validation of a panel of six TAAs to which autoantibodies have been described is reported here.

Materials and methods: Three separate groups of patients with newly diagnosed lung cancer were identified, along with control individuals, and their samples used to validate an enzyme-linked immunosorbant assay. Precision, linearity, assay reproducibility and antigen batch reproducibility were all assessed.

Results: For between-replicate error, samples with higher signals gave coefficients of variation (CVs) in the range 7%–15%. CVs for between-plate variation were only 1%–2% higher. For between-run error, CVs were in the range 15%–28%. In linearity studies, the slope was close to 1.0 and correlation coefficient values were generally >0.8. The sensitivity and specificity of individual batches of antigen varied slightly between groups of patients; however, the sensitivity and specificity of the panel of antigens as a whole remained constant. The validity of the calibration system was demonstrated.

Conclusions: A calibrated six-panel assay of TAAs has been validated for identifying nearly 40% of primary lung cancers via a peripheral blood test. Levels of reproducibility, precision and linearity would be acceptable for an assay used in a regulated clinical setting.

Tumor infiltrating lymphocytes but not serum pituitary antibodies are associated with poor clinical outcome after surgery in patients with pituitary adenoma

CONTEXT

Serum pituitary antibodies (Pit Abs) and tumor-infiltrating lymphocytes (TILs) have been described in pituitary adenomas, but their clinical significance remains unknown.

OBJECTIVE

The objective of the study was to assess Pit Abs and TILs prevalence in pituitary adenomas and their influence on clinical outcome.

DESIGN

This was a prevalence case-control study.

PATIENTS AND SETTING

Two hundred ninety-one pituitary adenoma cases (110 non-secreting, 30 ACTH-69 GH-71 prolactin- and 13 TSH-secreting adenoma; 177 operated and 114 untreated), 409 healthy controls, and 14 autoimmune hypophysitis were enrolled in a tertiary referral center.

INTERVENTION

Pit Abs were measured using immunofluorescence in all cases and controls (n = 714). The presence of TILs was evaluated using CD45 staining in a subset of adenomas surgically treated (n = 72).

MAIN OUTCOME MEASURE

Clinical response of pituitary adenoma after surgery was evaluated.

RESULTS

Pit Abs prevalence was higher in adenomas (5.1%) than healthy subjects (0.7%, P < 0.0001) and lower than in autoimmune hypophysitis patients (57%, P < 0.0001). Similarly, TILs prevalence was higher in adenomas than normal pituitary (P = 0.01) and lower than in autoimmune hypophysitis (P < 0.0001). No correlation between Pit Abs and TILs was found (P = 0.78). A poor clinical outcome was more common in adenoma patients with TILs (11 of 18, 61%) than in those without (17 of 54, 31%, P = 0.026). Multivariate regression analysis identified the presence of TILs as independent prognostic factor for persistence/recurrence of pituitary adenoma.

CONCLUSIONS

TILs and Pit Abs are present in a significant number of pituitary adenoma patients. Cell-mediated immunity appears to be predictive of a less favorable clinical outcome.

Triosephosphate isomerase and peroxiredoxin 6, two novel serum markers for human lung squamous cell carcinoma

There is currently substantial interest in the identification of human tumor antigens for the diagnosis and immunotherapy of cancer. In our previous study, secretion character and up-regulation of triosephosphate isomerase were observed in lung squamous cell carcinoma, and autoantibodies against triosephosphate isomerase and peroxiredoxin 6 were detected in the sera from over 25% of patients, but in none of the healthy controls. In this study, peroxiredoxin 6 was also found at higher levels in the sera of the patients. Up-regulated triosephosphate isomerase and peroxiredoxin 6 were further validated by enzyme-linked immunosorbent assay in an additional 61 lung squamous cell carcinoma patients, 23 lung adenocarcinoma patients, 56 other types of carcinoma patients, 12 benign lung disease patients, and 59 healthy controls. We found that both triosephosphate isomerase and peroxiredoxin 6 were specifically elevated in lung squamous cell carcinoma sera compared with other groups, with the exception of peroxiredoxin 6 in lung adenocarcinoma patients. Positive correlation between triosephosphate isomerase and distant metastasis was found. At the cut-off point 0.221 (optical density value) on the receiver operating characteristic curve, triosephosphate isomerase could comparatively discriminate lung squamous cell carcinoma from healthy controls with a sensitivity of 65.6%, specificity 84.7%, and total accuracy 75%. For peroxiredoxin 6, at the cut-off point 0.151, it could discriminate the two groups with a sensitivity of 70.5%, specificity 62.7%, and total accuracy 65.8%. With both triosephosphate isomerase and peroxiredoxin 6, discriminant analysis results showed that 68.9% of the lung squamous cell carcinoma and 83.1% of healthy controls were correctly classified. We concluded that triosephosphate isomerase and peroxiredoxin 6 could be markers for lung squamous cell carcinoma.

Genomic and proteomic biomarkers for cancer: a multitude of opportunities

Biomarkers are molecular indicators of a biological status, and as biochemical species can be assayed to evaluate the presence of cancer and therapeutic interventions. Through a variety of mechanisms cancer cells provide the biomarker material for their own detection. Biomarkers may be detectable in the blood, other body fluids, or tissues. The expectation is that the level of an informative biomarker is related to the specific type of disease present in the body. Biomarkers have potential both as diagnostic indicators and monitors of the effectiveness of clinical interventions. Biomarkers are also able to stratify cancer patients to the most appropriate treatment. Effective biomarkers for the early detection of cancer should provide a patient with a better outcome which in turn will translate into more efficient delivery of healthcare. Technologies for the early detection of cancer have resulted in reductions in disease-associated mortalities from cancers that are otherwise deadly if allowed to progress. Such screening technologies have proven that early detection will decrease the morbidity and mortality from cancer. An emerging theme in biomarker research is the expectation that panels of biomarker analytes rather than single markers will be needed to have sufficient sensitivity and specificity for the presymptomatic detection of cancer. Biomarkers may provide prognostic information of disease enabling interventions using targeted therapeutic agents as well as course-corrections in cancer treatment. Novel genomic, proteomic and metabolomic technologies are being used to discover and validate tumor biomarkers individually and in panels.

Detecting tumor-specific autoantibodies for cancer diagnosis: a technology overview

BACKGROUND

Studies on the autoantibody (humoral immune) response to tumor-associated aberrant cellular components have provided critical information about an individual's disease state. Tumor-specific autoantibodies detected in human serum samples are being studied extensively to determine their utility in developing serological diagnostic assays for cancer. The development of accurate panels of diagnostic markers for cancer detection is now being pursued using new technologies and tailored computational methods capable of analyzing data generated from large-scale biomarker discovery projects.

OBJECTIVE

In this technical overview, current methodologies being applied to the identification and characterization of tumor-specific autoantibodies in cancer patients' sera are reviewed.

METHODS

A variety of research approaches are presented that are now being used or have the potential to evaluate large numbers of patient sera for the presence of tumor-specific autoantibodies. Each approach is discussed regarding its primary attributes (advantages and limitations) that could lead to serological diagnostic assays for the early detection of cancer.

CONCLUSION

Preliminary results in the development of serological diagnostic assays have demonstrated that the basic experimental tools to accomplish this goal exist. In the future, autoantibody patterns against tumor-specific proteins may achieve high specificity and sensitivity for diagnosing disease in screening populations. The development of highly accurate reliable assays is a prerequisite for this technology to be integrated into clinically applicable strategies in patient care.

Aberrant tumor-associated antigen autoantibody profiles in healthy controls detected by multiplex bead-based immunoassay

There is an increasing amount of emphasis being placed on serological biomarkers as tools for early detection of various cancers. In addition to the tumor-related circulating antigens under current investigation, autoantibodies to tumor-associated antigens are emerging as alternative candidates due to their potential high sensitivity and specificity. Already a number of specific autoantibodies have been identified and several groups have reported on the ability of panels of autoantibodies to discriminate malignant from non-malignant conditions. In this investigation we evaluate tumor-associated antigen autoantibody profiles in a group of healthy individuals. We identify a subset of individuals that demonstrate high levels of autoantibody production across the spectrum of tumor-associated antigens tested. We conclude that this observation is a result of undefined non-malignant autoimmune stimulation. Our findings may be an indication of factors present in the general population that may confound multiplex autoantibody-based diagnostic tests by reducing assay specificity. Such factors will require further characterization and the development of adequate controls in order to improve the performance of diagnostic tests.

Proteomics and cancer epidemiology

Profiling of differentially expressed proteins is perhaps the most important and useful approach in developing tools for risk assessment in a population, diagnostic screening, and therapeutics. Proteomic markers have potential for identifying individuals at high risk of developing cancer; however, these markers have not been extensively used in cancer epidemiologic studies. Several markers have to be clinically validated. In this chapter, methods used in proteomic analysis of clinical samples, challenges in the proteomics and cancer epidemiology, and their potential solutions are discussed.

The footprints of cancer development: Cancer biomarkers

Diagnostic detection and measurement of cancer disease progression are essential elements for successful cancer disease management. The early stages of cancer development carry the maximum potential for therapeutic interventions. However, these stages are often asymptomatic, leading to delayed diagnosis at the very advanced stages when effective treatments are unavailing. The application of biomarkers to cancer is leading the way because of the unique association of genomic changes in cancer cells with the disease process. They have the potential to not only help identify who will develop cancer but also to predict as to when the event is most likely to occur. In recent years, there has been an enormous effort to develop specific and sensitive biomarkers for precise and accurate screening, diagnosis, prognosis and monitoring of high risk cancer to assist with therapeutic decisions. The present article is a brief review of the emerging trends in the development of biomarkers for early detection and precise evaluation of cancer disease.

Seromic analysis of antibody responses in non-small cell lung cancer patients and healthy donors using conformational protein arrays

Analysis of antibody responses to self-antigens has driven the development of the field of tumor immunology, with the identification of many protein targets found in cancer but with limited expression in normal tissues. Protein microarray technologies offer an unprecedented platform to assay the serological response of cancer patients to tumor antigens in a comprehensive fashion, against many proteins simultaneously. We developed an array containing 329 full-length proteins, originally identified as antigenic in various cancer patients by serological expression cloning (SEREX), that were immobilized as folded, functional products accessible for antibody binding. To validate the use of these microarrays, we selected 31 sera from non-small cell lung cancer patients previously known to react to the following antigens by ELISA: LAGE-1/CTAG2, MAGEA4, TP53, SSX and SOX2. These sera were compared with 22 sera from healthy donors for reactivity against a series of antigens present on microarrays. The sensitivity and specificity of the arrays compared favorably with standard ELISA techniques (94% concordance). We present here a stringent strategy for data analysis and normalization that is applicable to protein arrays in general, and describe findings suggesting that this approach is suitable for defining potential antigenic targets for cancer vaccine development, serum antibody signatures with clinical value, characterization of predictive serum markers for experimental therapeutics, and eventually for the serological definition of the cancer proteome (seromics).

Applications of protein microarrays for biomarker discovery

The search for new biomarkers for diagnosis, prognosis, and therapeutic monitoring of diseases continues in earnest despite dwindling success at finding novel reliable markers. Some of the current markers in clinical use do not provide optimal sensitivity and specificity, with the prostate cancer antigen (PSA) being one of many such examples. The emergence of proteomic techniques and systems approaches to study disease pathophysiology has rekindled the quest for new biomarkers. In particular the use of protein microarrays has surged as a powerful tool for large-scale testing of biological samples. Approximately half the reports on protein microarrays have been published in the last two years especially in the area of biomarker discovery. In this review, we will discuss the application of protein microarray technologies that offer unique opportunities to find novel biomarkers.

Toward an early diagnosis of lung cancer: an autoantibody signature for squamous cell lung carcinoma

Serum-based diagnosis offers the prospect of early lung carcinoma detection and of differentiation between benign and malignant nodules identified by CT. One major challenge toward a future blood-based diagnostic consists in showing that seroreactivity patterns allow for discriminating lung cancer patients not only from normal controls but also from patients with non-tumor lung pathologies. We addressed this question for squamous cell lung cancer, one of the most common lung tumor types. Using a panel of 82 phage-peptide clones, which express potential autoantigens, we performed serological spot assay. We screened 108 sera, including 39 sera from squamous cell lung cancer patients, 29 sera from patients with other non-tumor lung pathologies, and 40 sera from volunteers without known disease. To classify the serum groups, we employed the standard Naïve Bayesian method combined with a subset selection approach. We were able to separate squamous cell lung carcinoma and normal sera with an accuracy of 93%. Low-grade squamous cell lung carcinoma were separated from normal sera with an accuracy of 92.9%. We were able to distinguish squamous cell lung carcinoma from non-tumor lung pathologies with an accuracy of 83%. Three phage-peptide clones with sequence homology to ROCK1, PRKCB1 and KIAA0376 reacted with more than 15% of the cancer sera, but neither with normal nor with non-tumor lung pathology sera. Our study demonstrates that seroreactivity profiles combined with statistical classification methods have great potential for discriminating patients with squamous cell lung carcinoma not only from normal controls but also from patients with non-tumor lung pathologies.

Microarray methods for protein biomarker detection

The application of protein biomarkers as an aid for the detection and treatment of diseases has been subject to intensified interest in recent years. The quantitative assaying of protein biomarkers in easily obtainable biological fluids such as serum and urine offers the opportunity to improve patient care via earlier and more accurate diagnoses in a convenient, non-invasive manner as well as providing a potential route towards more individually targeted treatment. Essential to achieving progress in biomarker technology is the ability to screen large numbers of proteins simultaneously in a single experiment with high sensitivity and selectivity. In this article, we highlight recent progress in the use of microarrays for high-throughput biomarker profiling and discuss some of the challenges associated with these efforts.

Advances in genomic and proteomic studies of non-small-cell lung cancer: clinical and translational research perspective

Recent years have brought tremendous progress in the development of genomic and proteomic platforms to study cancer biology. Tests based on these platforms are helpful in early diagnosis, prognosis, and prediction of treatment benefit. Molecular studies performed on minimally invasive material (plasma, sputum) from individuals participating in longitudinal or case-control studies have approximately 70%-90% sensitivity and specificity to detect lung cancer. In operable non-small-cell lung cancer, genomic and proteomic studies yield better prognostic information than pathologic staging. There are several examples of successful identification of predictive assays for benefit from chemotherapy (ERCC1, RRM1, p27Kip1, and p53 expression) or targeted therapies (epidermal growth factor receptor [EGFR] gene copy number, EGFR activating mutations, EGFR protein expression, serum proteomic profile). These markers should be prospectively tested in clinical studies before they can be routinely used in the clinic.

Autoantibody approach for serum-based detection of head and neck cancer

Currently, no effective tool exists for screening or early diagnosis of head and neck squamous cell carcinoma (HNSCC). Here, we describe an approach for cancer detection based on analysis of patterns of serum immunoreactivity against a panel of biomarkers selected using microarray-based serologic profiling and specialized bioinformatics. We biopanned phage display libraries derived from three different HNSCC tissues to generate 5,133 selectively cloned tumor antigens. Based on their differential immunoreactivity on protein microarrays against serum immunoglobulins from 39 cancer and 41 control patients, we reduced the number of clones to 1,021. The performance of a neural network model (Multilayer Perceptron) for cancer classification on a data set of 80 HNSCC and 78 control samples was assessed using 10-fold cross-validation repeated 100 times. A panel of 130 clones was found to be adequate for building a classifier with sufficient sensitivity and specificity. Using these 130 markers on a completely new and independent set of 80 samples, an accuracy of 84.9% with sensitivity of 79.8% and specificity of 90.1% was achieved. Similar performance was achieved by reshuffling of the data set and by using other classification models. The performance of this classification approach represents a significant improvement over current diagnostic accuracy (sensitivity of 37% to 46% and specificity of 24%) in the primary care setting. The results shown here are promising and show the potential use of this approach toward eventual development of diagnostic assay with sufficient sensitivity and specificity suitable for detection of early-stage HNSCC in high-risk populations.