Profiling tumor-associated antibodies for early detection of non-small cell lung cancer. J Thorac Oncol. 2006;1:513-519. [PMID: 17409910 DOI: 10.1016/s1556-0864(15)30352-x]

Giant Magnetoresistance Based Biosensors for Cancer Screening and Detection

Early-stage screening of cancer is critical in preventing its development and therefore can improve the prognosis of the disease. One accurate and effective method of cancer screening is using high sensitivity biosensors to detect optically, chemically, or magnetically labeled cancer biomarkers. Among a wide range of biosensors, giant magnetoresistance (GMR) based devices offer high sensitivity, low background noise, robustness, and low cost. With state-of-the-art micro- and nanofabrication techniques, tens to hundreds of independently working GMR biosensors can be integrated into fingernail-sized chips for the simultaneous detection of multiple cancer biomarkers (i.e., multiplexed assay). Meanwhile, the miniaturization of GMR chips makes them able to be integrated into point-of-care (POC) devices. In this review, we first introduce three types of GMR biosensors in terms of their structures and physics, followed by a discussion on fabrication techniques for those sensors. In order to achieve target cancer biomarker detection, the GMR biosensor surface needs to be subjected to biological decoration. Thus, commonly used methods for surface functionalization are also reviewed. The robustness of GMR-based biosensors in cancer detection has been demonstrated by multiple research groups worldwide and we review some representative examples. At the end of this review, the challenges and future development prospects of GMR biosensor platforms are commented on. With all their benefits and opportunities, it can be foreseen that GMR biosensor platforms will transition from a promising candidate to a robust product for cancer screening in the near future.

Diagnostic value of tumor-associated autoantibodies panel in combination with traditional tumor markers for lung cancer

Introduction

The diagnostic value of 7 tumor-associated autoantibodies (AABs) including p53, PGP9.5, SOX2, GAGE7, GBU4-5, MEGEA1, and CAGE for the detection of lung cancer has shown inconsistency in several studies. This study aimed to confirm the diagnostic value of 7AABs and to explore whether the diagnostic value would be improved by combining them with 7 traditional tumor-associated antigens (CEA, NSE, CA125, SCC, CA15-3, pro-GRP, and CYFRA21-1) in clinical settings.

Methods

The plasma levels of 7-AABs were detected by enzyme-linked immunosorbent assay (ELISA) in 533 lung cancer cases and 454 controls. The 7 tumor antigens (7-TAs) were measured by Electrochemiluminescence immunoassay with Cobas 6000 (Roche, Basel, Switzerland).

Results

The positive rate of 7-AABs in the lung cancer group (64.00%) was significantly higher than that of healthy controls (47.90%). The 7-AABs panel was able to discriminate lung cancer from controls with a specificity of 51.50%. After combining the 7-AABs with 7-TAs, the sensitivity showed a significantly enhancement compared with 7AABs panel alone (92.09% vs 63.21%). In patients with resectable lung cancer, the combination of 7-AABs and 7-TAs improved the sensitivity from 63.52% to 97.42.

Discussion

In conclusion, our study found that the diagnostic value of 7-AABs was enhanced when combined with 7-TAs. This combined panel could be used as promising biomarker to detect resectable lung cancer in clinical settings.

Assessment of background levels of autoantibodies as a prognostic marker for severe SARS-CoV-2 infection

Background:

Patients with more severe forms of SARS-CoV-2 exhibit activation of immunological cascades. Participants (current or ex-smokers with at least 20 years pack history) in a trial (Early Diagnosis of Lung Cancer, Scotland [ECLS]) of autoantibody detection to predict lung cancer risk had seven autoantibodies measured 5 years before the pandemic. This study compared the response to Covid infection in study participants who tested positive and negative to antibodies to tumour-associated antigens: p53, NY-ESO-1, CAGE, GBU4-5, HuD, MAGE A4 and SOX2.

Methods:

Autoantibody data from the ECLS study was deterministically linked to the EAVE II database, a national, real-time prospective cohort using Scotland’s health data infrastructure, to describe the epidemiology of SARS-CoV-2 infection, patterns of healthcare use and outcomes. The strength of associations was explored using a network algorithm for exact contingency table significance testing by permutation.

Results:

There were no significant differences discerned between SARS-CoV-2 test results and EarlyCDT-Lung test results (p = 0.734). An additional analysis of intensive care unit (ICU) admissions detected no significant differences between those who tested positive and negative. Subgroup analyses showed no difference in COVID-19 positivity or death rates amongst those diagnosed with chronic obstructive pulmonary disease (COPD) with positive and negative EarlyCDT results.

Conclusions:

This hypothesis-generating study demonstrated no clinically valuable or statistically significant associations between EarlyCDT positivity in 2013-15 and the likelihood of SARS-CoV-2 positivity in 2020, ICU admission or death in all participants (current or ex-smokers with at least 20 years pack history) or in those with COPD or lung cancer.

Blood-based biomarkers for early detection of esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor of the digestive system worldwide, especially in China. Due to the lack of effective early detection methods, ESCC patients often present at an advanced stage at the time of diagnosis, which seriously affects the prognosis of patients. At present, early detection of ESCC mainly depends on invasive and expensive endoscopy and histopathological biopsy. Therefore, there is an unmet need for a non-invasive method to detect ESCC in the early stages. With the emergence of a large class of non-invasive diagnostic tools, serum tumor markers have attracted much attention because of their potential for detection of early tumors. Therefore, the identification of serum tumor markers for early detection of ESCC is undoubtedly one of the most effective ways to achieve early diagnosis and treatment of ESCC. This article reviews the recent advances in the discovery of blood-based ESCC biomarkers, and discusses the origins, clinical applications, and technical challenges of clinical validation of various types of biomarkers.

Autoantibodies: Potential clinical applications in early detection of esophageal squamous cell carcinoma and esophagogastric junction adenocarcinoma

Esophageal squamous cell carcinoma (ESCC) and esophagogastric junction adenocarcinoma (EGJA) are the two main types of gastrointestinal cancers that pose a huge threat to human health. ESCC remains one of the most common malignant diseases around the world. In contrast to the decreasing prevalence of ESCC, the incidence of EGJA is rising rapidly. Early detection represents one of the most promising ways to improve the prognosis and reduce the mortality of these cancers. Current approaches for early diagnosis mainly depend on invasive and costly endoscopy. Non-invasive biomarkers are in great need to facilitate earlier detection for better clinical management of patients. Tumor-associated autoantibodies can be detected at an early stage before manifestations of clinical signs of tumorigenesis, making them promising biomarkers for early detection and monitoring of ESCC and EGJA. In this review, we summarize recent insights into the iden-tification and validation of tumor-associated autoantibodies for the early detection of ESCC and EGJA and discuss the challenges remaining for clinical validation.

Analysis of Cytokine Pattern in Exhaled Breath Condensate of Patients with Squamous Cell Lung Carcinoma

Exhaled breath condensate (EBC) analysis is a promising method for investigating airway pathology. In this study we compared the cytokine pattern of EBC of patients suffering from squamous cell lung carcinoma with that of healthy smokers. Breath condensates collected from 8 smoking lung cancer patients before receiving any anticancer treatment and 8 smokers without any clinical or radiological evidence of pulmonary tumors were used for antibody microarray analysis testing 120 cytokines simultaneously. Ninety-eight cytokines on the array gave a detectable signal in both groups. Cytokine levels were similar across the samples, and none of the cytokines exhibited a significant increase or decrease in cancer patients as compared to healthy subjects with similar smoking status, lung function, and airway inflammation. The results of this pilot study suggest that patients with squamous cell lung carcinoma cannot be distinguished from smokers with no pulmonary tumors based on EBC cytokine signals only.

Detection of epitopes in systemic lupus erythematosus using peptide microarray

Systemic lupus erythematosus (SLE) is a common autoimmune disease, which features the secretion of antibodies directed against autoantigens in vivo. In the present study, a peptide microarray was developed to detect the epitopes recognized by autoantibodies in patients with SLE for an effective method of diagnosis. SLE-associated epitopes in 14 autoantigens were predicted using the antigenic epitope prediction software DNA star. Peptides were synthesized based on the predicted antigenic epitopes and immobilized on a slide surface and developed into a peptide microarray. Using this peptide microarray the autoantibodies in 120 patients with SLE and 110 healthy subjects were detected. A total of 73 potential antigenic epitopes in 14 autoantigens were predicted and screened. The peptide microarray based on the 73 epitopes was used to detect the autoantibodies in patients with SLE. A total of 14 epitopes with potential diagnostic values were screened out. The sensitivity and specificity of the 14 epitopes for the diagnosis of SLE were 71.6 and 85.8%, respectively. An optimal set of epitopes for SLE diagnosis was obtained. As individual patients had a specific autoantibody spectrum it was possible to detect autoantibodies in SLE and perform the diagnosis of SLE using the peptide microarray.

Significance of tumor-associated autoantibodies in the early diagnosis of lung cancer

OBJECTIVES

Autoantibodies tumor-associated antigens (TAAs) could be a valuable tool for the diagnosis or early detection of cancer due to their relatively high specificity and stability. The purpose of this study is to detect the level of tumor-associated autoantibodies in lung cancer and assess the diagnostic potential of autoantibodies in screening strategy for early stage lung cancer.

MATERIALS AND METHODS

Levels of tumor-associated autoantibodies (AAbs) were measured against a panel of seven TAAs (p53, PGP9.5, SOX2, GAGE7, GBU4-5, CAGE and MAGEA1) in 397 patients with pulmonary lesions (305 with newly diagnosis of NSCLC, 47 with SCLC and 45 with benign nodule) and 74 control persons without any nodules in the lung after chest MDCT scan. The sensitivity, specificity for patients and control persons, positive rate of the panel in different pathology, stage, size of lesion, age and gender were compared and analyzed.

RESULTS

The AAbs panel could distinguish malignant lesions from benign lesions and control people, with sensitivity of 56.53% and specificity of 91.60%. The specificity could be further increased to 95.80%, when combined with CT. The AAbs also showed high diagnostic value of malignant nodule, and it would be a new method for judgment of malignant nodules that are less than 8 mm in diameter. No significant differences were seen based on pathology, NSCLC stages, tumor size, age or gender.

CONCLUSION

This assay confirms the value of AAbs panel as a diagnostic tool combined with CT scan.

An Autoantibody Against Human DNA-Topoisomerase I Is a Novel Biomarker for Non-Small Cell Lung Cancer

BACKGROUND

We previously reported a novel tumor-associated antigen with a molecular weight of approximately 48 kDa that was a fragment derived from human DNA-topoisomerase I. The aim of this study is to further investigate the clinical significance of the autoantibody in patients with non-small cell lung cancer (NSCLC).

METHODS

We determined serum levels of the autoantibody in 127 NSCLC patients, 127 age-, sex-, and smoking history-matched healthy control subjects, and 38 patients with pulmonary benign tumors by using a specific enzyme linked immunosorbent assay for the autoantibody. We then statistically evaluated its clinical application value.

RESULTS

Serum levels of the autoantibody in NSCLC patients were significantly higher than in healthy control subjects and patients with benign tumors (p = 0.001). The percentage of sera with a positive level of the autoantibody was 71.8%, 65.6%, 41.9%, and 48.0% in stages I, II, III, and IV of the cancer, respectively (p = 0.049). The area under the receiver-operating characteristics curve was 0.971 (95% confidence interval: 0.953 to 0988) for healthy controls and patients with benign tumors versus early stage NSCLC patients. Moreover, the overall survival rate of the patients in stages I, II, and IV with negative levels of the autoantibody was significantly lower than that of patients with positive levels of the autoantibody (p = 0.013, 0.023, and 0.047 for stages I, II, and IV, respectively).

CONCLUSIONS

Our results indicate that the autoantibody can be used as a novel biomarker for the early diagnosis and prognosis of NSCLC.

Longitudinal Monitoring of Antibody Responses against Tumor Cells Using Magneto-nanosensors with a Nanoliter of Blood

Each immunoglobulin isotype has unique immune effector functions. The contribution of these functions in the elimination of pathogens and tumors can be determined by monitoring quantitative temporal changes in isotype levels. Here, we developed a novel technique using magneto-nanosensors based on the effect of giant magnetoresistance (GMR) for longitudinal monitoring of total and antigen-specific isotype levels with high precision, using as little as 1 nL of serum. Combining in vitro serologic measurements with in vivo imaging techniques, we investigated the role of the antibody response in the regression of firefly luciferase (FL)-labeled lymphoma cells in spleen, kidney, and lymph nodes in a syngeneic Burkitt's lymphoma mouse model. Regression status was determined by whole body bioluminescent imaging (BLI). The magneto-nanosensors revealed that anti-FL IgG2a and total IgG2a were elevated and sustained in regression mice compared to non-regression mice (p < 0.05). This platform shows promise for monitoring immunotherapy, vaccination, and autoimmunity.

Screening and Biosensor-Based Approaches for Lung Cancer Detection

Early diagnosis of lung cancer helps to reduce the cancer death rate significantly. Over the years, investigators worldwide have extensively investigated many screening modalities for lung cancer detection, including computerized tomography, chest X-ray, positron emission tomography, sputum cytology, magnetic resonance imaging and biopsy. However, these techniques are not suitable for patients with other pathologies. Developing a rapid and sensitive technique for early diagnosis of lung cancer is urgently needed. Biosensor-based techniques have been recently recommended as a rapid and cost-effective tool for early diagnosis of lung tumor markers. This paper reviews the recent development in screening and biosensor-based techniques for early lung cancer detection.

Identifying gene-gene interactions using penalized tensor regression

Gene-gene (G×G) interactions have been shown to be critical for the fundamental mechanisms and development of complex diseases beyond main genetic effects. The commonly adopted marginal analysis is limited by considering only a small number of G factors at a time. With the "main effects, interactions" hierarchical constraint, many of the existing joint analysis methods suffer from prohibitively high computational cost. In this study, we propose a new method for identifying important G×G interactions under joint modeling. The proposed method adopts tensor regression to accommodate high data dimensionality and the penalization technique for selection. It naturally accommodates the strong hierarchical structure without imposing additional constraints, making optimization much simpler and faster than in the existing studies. It outperforms multiple alternatives in simulation. The analysis of The Cancer Genome Atlas (TCGA) data on lung cancer and melanoma demonstrates that it can identify markers with important implications and better prediction performance.

Early detection of lung cancer by using an autoantibody panel in Chinese population

We have previously identified a panel of autoantibodies (AABs), including p53, GAGE7, PGP9.5, CAGE, MAGEA1, SOX2 and GBU4-5, that was helpful in the early diagnosis of lung cancer. This large-scale, multicenter study was undertaken to validate the clinical value of this 7-AABs panel for early detection of lung cancer in a Chinese population. Two independent sets of plasma samples from 2308 participants were available for the assay of AABs (training set = 300; validation set = 2008). The concentrations of AABs were quantitated by enzyme-linked immunosorbent assay (ELISA), and the optimal cutoff value for each AAB was determined in the training set and then applied in the validation set. The value of the 7-AABs panel for the early detection of lung cancer was assessed in 540 patients who presented with ground-glass nodules (GGNs) and/or solid nodules. In the validation set, the sensitivity and specificity of the 7-AABs panel were 61% and 90%, respectively. For stage I and stage II non-small cell lung cancer (NSCLC), the sensitivity of the 7-AABs panel was 62% and 59%, respectively, and for limited stage small cell lung cancer (SCLC) it was 59%; these sensitivity values were considerably higher than for traditional biomarkers (including CEA, NSE and CYFRA21-1). Importantly, the combination of the 7-AABs panel and low-dose computed tomography (CT) scanning significantly improved the diagnostic yield in patients presenting with GGNs and/or solid nodules. In conclusion, our 7-AABs panel has clinical value for early detection of lung cancer, including early-stage lung cancer presenting as GGNs.

Progress and prospects of early detection in lung cancer

Lung cancer is the leading cause of cancer-related death in the world. It is broadly divided into small cell (SCLC, approx. 15% cases) and non-small cell lung cancer (NSCLC, approx. 85% cases). The main histological subtypes of NSCLC are adenocarcinoma and squamous cell carcinoma, with the presence of specific DNA mutations allowing further molecular stratification. If identified at an early stage, surgical resection of NSCLC offers a favourable prognosis, with published case series reporting 5-year survival rates of up to 70% for small, localized tumours (stage I). However, most patients (approx. 75%) have advanced disease at the time of diagnosis (stage III/IV) and despite significant developments in the oncological management of late stage lung cancer over recent years, survival remains poor. In 2014, the UK Office for National Statistics reported that patients diagnosed with distant metastatic disease (stage IV) had a 1-year survival rate of just 15-19% compared with 81-85% for stage I.

Systematic review: Tumor-associated antigen autoantibodies and ovarian cancer early detection

OBJECTIVES

Tumor-associated autoantibodies (AAbs), produced as an immune response to tumor-associated antigens (TAAs), are a novel pathway of early detection markers.

METHODS

We conducted a systematic review on AAbs and ovarian cancer to summarize the diagnostic performance of individual AAbs and AAb panels. A total of 29 studies including 85 AAbs were included; 27 of the studies were conducted in prevalent cases and cancer-free controls and 2 investigations included pre-diagnosis samples. The majority of studies were hypothesis-driven, evaluating AAbs to target TAAs; 10 studies used screening approaches such as serological expression cloning (SEREX) and nucleic acid-programmable protein arrays (NAPPA).

RESULTS

The highest sensitivities for individual AAbs were reported for RhoGDI-AAbs (89.5%) and TUBA1C-AAbs (89%); however, specificity levels were relatively low (80% and 75%, respectively). High sensitivities at high specificities were reported for HOXA7-AAbs for detection of moderately differentiated ovarian tumors (66.7% sensitivity at 100% specificity) and IL8-AAbs in stage I-II ovarian cancer (65.5% sensitivity at 98% specificity). A panel of 11 AAbs (ICAM3, CTAG2, p53, STYXL1, PVR, POMC, NUDT11, TRIM39, UHMK1, KSR1, and NXF3) provided 45% sensitivity at 98% specificity for serous ovarian cancer, when at least 2 AAbs were above a threshold of 95% specificity. Twelve of the AAbs identified in this review were investigated in more than one study. Data on diagnostic discrimination by tumor histology and stage at diagnosis are sparse. Limited data suggest select AAb markers improve diagnostic discrimination when combined with markers such as CA125 and HE4.

CONCLUSIONS

AAbs for ovarian cancer early detection is an emerging area, and large-scale, prospective investigations considering histology and stage are required for discovery and validation. However, data to date suggests panels of AAbs may eventually reach sufficient diagnostic discrimination to allow earlier detection of disease as a complement to existing markers and transvaginal ultrasound.

BARD1 serum autoantibodies for the detection of lung cancer

PURPOSE

Currently the screening for lung cancer for risk groups is based on Computed Tomography (CT) or low dose CT (LDCT); however, the lung cancer death rate has not decreased significantly with people undergoing LDCT. We aimed to develop a simple reliable blood test for early detection of all types of lung cancer based on the immunogenicity of aberrant forms of BARD1 that are specifically upregulated in lung cancer.

METHODS

ELISA assays were performed with a panel of BARD1 epitopes to detect serum levels of antibodies against BARD1 epitopes. We tested 194 blood samples from healthy donors and lung cancer patients with a panel of 40 BARD1 antigens. Using fitted Lasso logistic regression we determined the optimal combination of BARD1 antigens to be used in ELISA for discriminating lung cancer from healthy controls. Random selection of samples for training sets or validations sets was applied to validate the accuracy of our test.

RESULTS

Fitted Lasso logistic regression models predict high accuracy of the BARD1 autoimmune antibody test with an AUC = 0.96. Validation in independent samples provided and AUC = 0.86 and identical AUCs were obtained for combined stages 1-3 and late stage 4 lung cancers. The BARD1 antibody test is highly specific for lung cancer and not breast or ovarian cancer.

CONCLUSION

The BARD1 lung cancer test shows higher sensitivity and specificity than previously published blood tests for lung cancer detection and/or diagnosis or CT scans, and it could detect all types and all stages of lung cancer. This BARD1 lung cancer test could therefore be further developed as i) screening test for early detection of lung cancers in high-risk groups, and ii) diagnostic aid in complementing CT scan.

The biomarker landscape in mycosis fungoides and Sézary syndrome

The practice of pre-emptive individualized medicine is predicated on the discovery, development and application of biomarkers in specific clinical settings. Mycosis fungoides and Sézary syndrome are the two most common type of cutaneous T-cell lymphoma, yet diagnosis, prognosis and disease monitoring remain a challenge. In this review, we discuss the current state of biomarker discovery in mycosis fungoides and Sézary syndrome, highlighting the most promising molecules in different compartments. Further, we emphasize the need for continued multicentre efforts to validate available and new biomarkers and to develop prospective combinatorial panels of already discovered molecules.

Identification of cancer-specific motifs in mimotope profiles of serum antibody repertoire

Background

For fighting cancer, earlier detection is crucial. Circulating auto-antibodies produced by the patient’s own immune system after exposure to cancer proteins are promising bio-markers for the early detection of cancer. Since an antibody recognizes not the whole antigen but 4–7 critical amino acids within the antigenic determinant (epitope), the whole proteome can be represented by a random peptide phage display library. This opens the possibility to develop an early cancer detection test based on a set of peptide sequences identified by comparing cancer patients’ and healthy donors’ global peptide profiles of antibody specificities.

Results

Due to the enormously large number of peptide sequences contained in global peptide profiles generated by next generation sequencing, the large number of cancer and control sera is required to identify cancer-specific peptides with high degree of statistical significance. To decrease the number of peptides in profiles generated by nextgen sequencing without losing cancer-specific sequences we used for generation of profiles the phage library enriched by panning on the pool of cancer sera. To further decrease the complexity of profiles we used computational methods for transforming a list of peptides constituting the mimotope profiles to the list motifs formed by similar peptide sequences.

Conclusion

We have shown that the amino-acid order is meaningful in mimotope motifs since they contain significantly more peptides than motifs among peptides where amino-acids are randomly permuted. Also the single sample motifs significantly differ from motifs in peptides drawn from multiple samples. Finally, multiple cancer-specific motifs have been identified.

Panel of autoantibodies against multiple tumor-associated antigens for detecting gastric cancer

Gastric cancer is the second leading cause of cancer death in the world, and effective diagnosis is extremely important for good outcome. We assessed the diagnostic potential of an autoantibody panel that may provide a novel tool for the early detection of gastric cancer. We analyzed data from patients with gastric cancer and normal controls in test and validation cohorts. Autoantibody levels were measured against a panel of six tumor‐associated antigens (TAAs) by ELISA: p53, heat shock protein 70, HCC‐22‐5, peroxiredoxin VI, KM‐HN‐1, and p90 TAA. We assessed serum autoantibodies in 100 participants in the test cohort. The validation cohort comprised 248 participants. Autoantibodies to at least one of the six antigens showed a sensitivity/specificity of 49.0% (95% confidence interval [CI], 39.2–58.8%)/92.4% (95% CI, 87.2–97.6%), and 52.0% (95% CI, 42.2–61.8%)/90.5% (95% CI, 84.8–96.3%) in the test and validation cohorts, respectively. In the validation cohort, no significant differences were seen when patients were subdivided based on age, sex, depth of tumor invasion, lymph node metastasis, distant metastasis, peritoneal dissemination, or TNM stage. Patients who were positive for more than two antibodies in the panel tended to have a worse prognosis than those who were positive for one or no antibody. Measurement of autoantibody response to multiple TAAs in an optimized panel assay to discriminate patients with early stage gastric cancer from normal controls may aid in the early detection of gastric cancer.

Autoantibodies: Opportunities for Early Cancer Detection

Cancer cells can induce an immunological response resulting in the production of tumor-associated (TA) autoantibodies. These serum immunobiomarkers have been detected for a range of cancers at an early stage before the development of clinical symptoms. Their measurement is minimally invasive and cost effective using established technologies. TA autoantibodies are present in a clinically significant number of individuals and could supplement current screening modalities to aid early diagnosis of high-risk populations and assist the clinical management of patients. Here we review their production, discovery, and validation as biomarkers for cancer and their current and future potential as clinical tools.

Serum tumor-associated autoantibodies as diagnostic biomarkers for lung cancer: A systematic review and meta-analysis

OBJECTIVE

We performed a comprehensive review and meta-analysis to evaluate the diagnostic values of serum single and multiplex tumor-associated autoantibodies (TAAbs) in patients with lung cancer (LC).

METHODS

We searched the MEDLINE and EMBASE databases for relevant studies investigating serum TAAbs for the diagnosis of LC. The primary outcomes included sensitivity, specificity and accuracy of the test.

RESULTS

The systematic review and meta-analysis included 31 articles with single autoantibody and 39 with multiplex autoantibodies. Enzyme-linked immunosorbent assay (ELISA) was the most common detection method. For the diagnosis of patients with all stages and early-stage LC, different single or combinations of TAAbs demonstrated different diagnostic values. Although individual TAAbs showed low diagnostic sensitivity, the combination of multiplex autoantibodies offered relatively high sensitivity. For the meta-analysis of a same panel of autoantibodies in patients at all stages of LC, the pooled results of the panel of 6 TAAbs (p53, NY-ESO-1, CAGE, GBU4-5, Annexin 1 and SOX2) were: sensitivity 38% (95% CI 0.35-0.40), specificity 89% (95% CI 0.86-0.91), diagnostic accuracy 65.9% (range 62.5-81.8%), AUC 0.52 (0.48-0.57), while the summary estimates of 7 TAAbs (p53, CAGE, NY-ESO-1, GBU4-5, SOX2, MAGE A4 and Hu-D) were: sensitivity 47% (95% CI 0.34-0.60), specificity 90% (95% CI 0.89-0.92), diagnostic accuracy 78.4% (range 67.5-88.8%), AUC 0.90 (0.87-0.93). For the meta-analysis of the same panel of autoantibodies in patients at early-stage of LC, the sensitivities of both panels of 7 TAAbs and 6 TAAbs were 40% and 29.7%, while their specificities were 91% and 87%, respectively.

CONCLUSIONS

Serum single or combinations of multiplex autoantibodies can be used as a tool for the diagnosis of LC patients at all stages or early-stage, but the combination of multiplex autoantibodies shows a higher detection capacity; the diagnostic value of the panel of 7 TAAbs is higher than the panel of 6 TAAbs, which may be used as potential biomarkers for the early detection of LC.

Cancer testis antigen SPAG9 is a promising marker for the diagnosis and treatment of lung cancer

Cancer testis antigen sperm-associated antigen 9 (SPAG9) is highly expressed in many types of cancers. In the present study, to obtain a better understanding of the relevance of SPAG9 in cancer diagnosis and treatment, the expression of SPAG9 mRNA and protein in lung cancer specimens was evaluated by RT-PCR, western blotting and immunohistochemistry. ELISA was used to quantify the SPAG9 autoantibody in the peripheral blood of lung cancer patients. The results showed that the expression of SPAG9 mRNA and protein in the lung cancer tissues was significantly higher than that in the adjacent non-cancerous tissues (P<0.01). The level of the SPAG9 autoantibody in the serum of lung cancer patients was significantly higher than the level in the healthy controls (P<0.001), and the level of the SPAG9 autoantibody in the serum of untreated patients was significantly higher than that in treated patients (P=0.002). SPAG9 IgG antibody levels were significantly lower in treated adenocarcinoma and small cell lung cancer patients than these levels in the untreated patients (P=0.006, P=0.026, respectively), while no statistical difference was found between treated and untreated squamous cell carcinoma patients. Our results suggest that the SPAG9 antibody in serum is a promising marker for the diagnosis of lung cancer, and the level of the humoral immune response to this antigen appears to be related to the type of lung cancer.

The challenge of small lung nodules identified in CT screening: can biomarkers assist diagnosis?

Various biomarkers have been developed as noninvasive tests to indicate the presence of lung cancer in asymptomatic persons, and in particular to provide evidence as to whether indeterminate lung nodules detected by screening are malignant. We performed an overview of the range of biomarkers reported in the literature and described those that can complement low-dose computed tomography screening. Several have promising sensitivity and specificity. However to our knowledge, only three techniques have reached the prospective screening phase (phase 4) of the five-phase biomarker development process. Two miRNA signatures (the miR-Test for serum and the miRNA signature classifier test for plasma) are being assessed in prospective screening trials, as is the EarlyCDT-Lung test based on autoantibodies. All will need to undergo prospective studies to determine their ability to improve outcomes before they can become an established adjunct to lung cancer control strategies.

Current clinical application of genomic and proteomic profiling in non-small-cell lung cancer

BACKGROUND

Genomic or proteomic profiling of cancer can be broadly defined as a systematic grouping of cancer based on its genetic or protein makeup. In the management of non-small-cell lung cancer (NSCLC), genomic and proteomic profiling applications have become useful in early disease detection, diagnosis, treatment, and prognostication.

METHODS

We reviewed the recent literature on the applications of genomic and proteomic profiling in NSCLC. Important applications were summarized into those already adopted as standard care and those still under investigation.

RESULTS

For genomic profiling, testing for EGFR mutation and ALK rearrangement has become routine for adenocarcinoma. Multiplex assay and malignancy-risk gene signature are both important applications in development. A test to predict outcome after treatment with an epidermal growth factor rector/tyrosine kinase inhibitor and a screening blood test for lung cancer are being investigated for use in proteomic profiling.

CONCLUSIONS

Genomic profiling is routine in patients with NSCLC, and proteomic profiling shows promise. Additional genomic and proteomic profiling applications may also prove to be useful contributions in the care of these patients.

Combination of autoantibodies against NY-ESO-1 and viral capsid antigen immunoglobulin A for improved detection of nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is one of the most common malignant tumors in Southern China and Southeast Asia, and early detection remains a challenge. Autoantibodies have been found to precede the manifestations of symptomatic cancer by several months to years, making their identification of particular relevance for early detection. In the present study, the diagnostic value of serum autoantibodies against NY-ESO-1 in NPC patients was evaluated. The study included 112 patients with NPC and 138 normal controls. Serum levels of autoantibodies against NY-ESO-1 and classical Epstein-Barr virus marker, viral capsid antigen immunoglobulin A (VCA-IgA), were measured by enzyme-linked immunosorbent assay. Measurement of autoantibodies against NY-ESO-1 and VCA-IgA demonstrated a sensitivity/specificity of 42.9/94.9% [95% confidence interval (CI), 33.7-52.6/89.4-97.8%] and 55.4/95.7% (95% CI, 45.7-64.7/90.4-98.2%), respectively. The area under receiver operating characteristic curve for autoantibodies against NY-ESO-1 (0.821; 95% CI, 0.771-0.871) was marginally lower than that for VCA-IgA (0.860; 95% CI, 0.810-0.910) in NPC. The combination of autoantibodies against NY-ESO-1 and VCA-IgA yielded an enhanced sensitivity of 80.4% (95% CI, 71.6-87.0%) and a specificity of 90.6% (95% CI, 84.1-94.7%). Moreover, detection of autoantibodies against NY-ESO-1 could differentiate early-stage NPC patients from normal controls. Our results suggest that autoantibodies against NY-ESO-1 may serve as a potential biomarker, as a supplement to VCA-IgA, for the screening and diagnosis of NPC.

Serum autoantibody measurement for the detection of hepatocellular carcinoma

Background

Individuals with liver disease, and especially those with Hepatitis B or C, are at an increased risk of developing hepatocellular carcinoma (HCC) which is the third most common cause of cancer-related death worldwide. Inadequate screening tests largely account for presentation of advanced tumours and high mortality rates. Early detection of HCC amongst high-risk groups is paramount in improving prognosis. This research aimed to further characterise the previously described humoral immune response raised to tumour-associated antigens (TAAs) in the serum of patients with HCC.

Methods

Serum from 96 patients with confirmed HCC, 96 healthy controls matched for age and sex, 78 patients with confirmed liver cirrhosis and 91 patients with confirmed chronic liver disease were analysed for the presence of IgG autoantibodies raised to 41 recombinant TAAs/antigen fragments by ELISA.

Results

Varying autoantibody specificities (97–100%) and sensitivities (0–10%) were observed to individual TAAs. A 21-antigen panel achieved a specificity of 92% and sensitivity of 45% for the detection of HCC. This same panel identified 21% of 169 high-risk controls as having elevated autoantibody levels. A reproducible panel of 10 antigens achieved a specificity of 91% and sensitivity of 41% in HCC. 15% of 152 high-risk controls gave positive results with this panel.

Conclusions

This minimally invasive blood test has the potential to offer advantages over currently available tools for the identification of HCC amongst pre-disposed patients. Results are comparable to current gold standards in HCC (Ultrasonography) and to similar tests in other cancers (EarlyCDT-Lung).

Peptides from the variable region of specific antibodies are shared among lung cancer patients

Late diagnosis of lung cancer is still the main reason for high mortality rates in lung cancer. Lung cancer is a heterogeneous disease which induces an immune response to different tumor antigens. Several methods for searching autoantibodies have been described that are based on known purified antigen panels. The aim of our study is to find evidence that parts of the antigen-binding-domain of antibodies are shared among lung cancer patients. This was investigated by a novel approach based on sequencing antigen-binding-fragments (Fab) of immunoglobulins using proteomic techniques without the need of previously known antigen panels. From serum of 93 participants of the NELSON trial IgG was isolated and subsequently digested into Fab and Fc. Fab was purified from the digested mixture by SDS-PAGE. The Fab containing gel-bands were excised, tryptic digested and measured on a nano-LC-Orbitrap-Mass-spectrometry system. Multivariate analysis of the mass spectrometry data by linear canonical discriminant analysis combined with stepwise logistic regression resulted in a 12-antibody-peptide model which was able to distinguish lung cancer patients from controls in a high risk population with a sensitivity of 84% and specificity of 90%. With our Fab-purification combined Orbitrap-mass-spectrometry approach, we found peptides from the variable-parts of antibodies which are shared among lung cancer patients.

Development of a multiplex autoantibody test for detection of lung cancer

Lung cancer is the leading cause of cancer-related deaths for both men and women. Early diagnosis of lung cancer has a 5-year survival rate of 48.8%, however, nearly 35% of stage I patients relapses after surgical resection, thus portending a poor prognosis. Therefore, detecting lung cancer in early stage and further identifying the high-risk patients would allow the opportunity to provide adjuvant therapy and possibly increase survival. There is considerable evidence that the immune system produces an autoantibody response to neoplastic cells. The detection of such autoantibodies has been shown to have diagnostic and prognostic value. Here we took advantage of the high-throughput Luminex technique to multiplex a total of 14 tumor-associated autoantigens to detect the autoantibody from the patients sera. The 14 antigens were expressed by in vitro transcription/translation system with HaloTag at N-terminus. The fusion proteins were then covalently immobilized onto the Luminex microspheres conjugated by the halo-link ligand, thus eliminating the protein purification procedure. Sera samples from cancer patients and healthy controls were interacted with the microsphere-antigen complex to measure the autoantibodies. We have developed a quick multiplex detection system for measuring autoantibody signature from patient sera with minimal cross-reaction. A panel of seven autoantibody biomarkers has generated an AUC>80% in distinguishing the lung cancers from healthy controls. This study is the first report by combining Luminex platform and HaloTag technology to detect humoral immune response in cancer patients. Due to the flexibility of the Luminex technology, this approach can be applied to others conditions such as infectious, neurological, and metabolic diseases. One can envision that this multiplex Luminex system as well as the panel of seven biomarkers could be used to screen the high-risk population with subsequent CT test based on the blood test result.

Autoantibody profiling for lung cancer screening longitudinal retrospective analysis of CT screening cohorts

Recommendations for lung cancer screening present a tangible opportunity to integrate predictive blood-based assays with radiographic imaging. This study compares performance of autoantibody markers from prior discovery in sample cohorts from two CT screening trials. One-hundred eighty non-cancer and 6 prevalence and 44 incidence cancer cases detected in the Mayo Lung Screening Trial were tested using a panel of six autoantibody markers to define a normal range and assign cutoff values for class prediction. A cutoff for minimal specificity and best achievable sensitivity were applied to 256 samples drawn annually for three years from 95 participants in the Kentucky Lung Screening Trial. Data revealed a discrepancy in quantile distribution between the two apparently comparable sample sets, which skewed the assay’s dynamic range towards specificity. This cutoff offered 43% specificity (102/237) in the control group and accurately classified 11/19 lung cancer samples (58%), which included 4/5 cancers at time of radiographic detection (80%), and 50% of occult cancers up to five years prior to diagnosis. An apparent ceiling in assay sensitivity is likely to limit the utility of this assay in a conventional screening paradigm. Pre-analytical bias introduced by sample age, handling or storage remains a practical concern during development, validation and implementation of autoantibody assays. This report does not draw conclusions about other logical applications for autoantibody profiling in lung cancer diagnosis and management, nor its potential when combined with other biomarkers that might improve overall predictive accuracy.

Profiling the IgOme: meeting the challenge

The entire repertoire of antibodies in our serum, the IgOme, is a historical record of our past experiences and a reflection of our immune status at any given moment. Understanding the dynamics of the IgOme and how the diversity and specificities of serum antibodies change in response to disease and maintenance of homeostasis can directly impact the ability to design and develop novel vaccines, diagnostics and therapeutics. Here we review both direct and indirect methodologies that are being developed to map the complexity and specificities of the antibodies in polyclonal serum - the IgOme.

Identification of novel autoantibodies for detection of malignant mesothelioma

Background

The malignant mesothelioma (MM) survival rate has been hampered by the lack of efficient and accurate early detection methods. The immune system may detect the early changes of tumor progression by responding with tumor-associated autoantibody production. Hence, in this study, we translated the humoral immune response to cancer proteins into a potential blood test for MM.

Methodology/Principal Findings

A T7 phage MM cDNA library was constructed using MM tumor tissues and biopanned for tumor-associated antigens (TAAs) using pooled MM patient and normal serum samples. About 1008 individual phage TAA clones from the biopanned library were subjected to protein microarray construction and tested with 53 MM and 52 control serum samples as a training group. Nine candidate autoantibody markers were selected from the training group using Tclass system and logistic regression statistical analysis, which achieved 94.3% sensitivity and 90.4% specificity with an AUC value of 0.89 in receiver operating characteristic analysis. The classifier was further evaluated with 50 patient and 50 normal serum samples as an independent blind validation, and the sensitivity of 86.0% and the specificity of 86.0% were obtained with an AUC of 0.82. Sequencing and BLASTN analysis of the classifier revealed that five of these nine candidate markers were found to have strong homology to cancer related proteins (PDIA6, MEG3, SDCCAG3, IGHG3, IGHG1).

Conclusions/Significance

Our results indicated that using a panel of 9 autoantibody markers presented a promising accuracy for MM detection. Although the results need further validation in high-risk groups, they provided the potentials in developing a serum-based assay for MM diagnosis.

Early lung cancer diagnosis by biosensors

Lung cancer causes an extreme threat to human health, and the mortality rate due to lung cancer has not decreased during the last decade. Prognosis or early diagnosis could help reduce the mortality rate. If microRNA and tumor-associated antigens (TAAs), as well as the corresponding autoantibodies, can be detected prior to clinical diagnosis, such high sensitivity of biosensors makes the early diagnosis and prognosis of cancer realizable. This review provides an overview of tumor-associated biomarker identifying methods and the biosensor technology available today. Laboratorial researches utilizing biosensors for early lung cancer diagnosis will be highlighted.

Early detection of NSCLC with scFv selected against IgM autoantibody

Survival of patients with lung cancer could be significantly prolonged should the disease be diagnosed early. Growing evidence indicates that the immune response in the form of autoantibodies to developing cancer is present before clinical presentation. We used a phage-displayed antibody library to select for recombinant scFvs that specifically bind to lung cancer-associated IgM autoantibodies. We selected for scFv recombinant antibodies reactive with circulating IgM autoantibodies found in the serum of patients with early stage lung adenocarcinoma but not matched controls. Discriminatory performance of 6 selected scFvs was validated in an independent set of serum from stage 1 adenocarcinoma and matching control groups using two independent novel methods developed for this application. The panel of 6 selected scFvs predicted cancer based on seroreactivity value with sensitivity of 0.8 and specificity of 0.87. Receiver Operative Characteristic curve (ROC) for combined 6 scFv has an AUC of 0.88 (95%CI, 0.76–1.0) as determined by fluorometric microvolume assay technology (FMAT) The ROC curve generated using a homogeneous bridging Mesa Scale Discovery (MSD) assay had an AUC of 0.72 (95% CI, 0.59–0.85). The panel of all 6 antibodies demonstrated better discriminative power than any single scFv alone. The scFv panel also demonstrated the association between a high score - based on seroreactivity - with poor survival. Selected scFvs were able to recognize lung cancer associated IgM autoantibodies in patient serum as early as 21 months before the clinical presentation of disease. The panel of antibodies discovered represents a potential unique non-invasive molecular tool to detect an immune response specific to lung adenocarcinoma at an early stage of disease.

Potential application of non-small cell lung cancer-associated autoantibodies to early cancer diagnosis

To identify a panel of tumor associated autoantibodies which can potentially be used as biomarkers for the early diagnosis of non-small cell lung cancer (NSCLC). Thirty-five unique and in-frame expressed phage proteins were isolated. Based on the gene expression profiling, four proteins were selected for further study. Both receiver operating characteristic curve analysis and leave-one-out method revealed that combined measurements of four antibodies produced have better predictive accuracies than any single marker alone. Leave-one-out validation also showed significant relevance with all stages of NSCLC patients. The panel of autoantibodies has a high potential for detecting early stage NSCLC.

Serological antibodies against LY6K as a diagnostic biomarker in esophageal squamous cell carcinoma

OBJECTIVES

To evaluate the diagnostic values of autoantibodies against lymphocyte antigen 6 complex locus K (LY6K) in esophageal squamous cell carcinoma (ESCC).

METHODS

After cloning, expressing, and purifying LY6K as fusion proteins, LY6K autoantibodies were measured in 62 patient and 58 control serum samples using enzyme-linked immunosorbent assay (ELISA). Reverse transcription polymerase chain reaction (RT-PCR) was used to measure the LY6K mRNA levels in ESCC and adjacent tissues.

RESULTS

LY6K autoantibodies were found significantly higher in patients than controls. The area under the receiver-operating characteristic (ROC) curve (AUC) was 0.85, and the optimal sensitivity and specificity for ESCC detection were 80.6 and 78.7%, respectively. LY6K mRNA expressions in patients were upregulated.

CONCLUSIONS

Autoantibodies against LY6K may be a good diagnostic biomarker for ESCC.

EarlyCDT®-Lung test: improved clinical utility through additional autoantibody assays

Tumor-associated autoantibodies (AAbs) have been described in patients with lung cancer, and the EarlyCDT®-Lung test that measures such AAbs is available as an aid for the early detection of lung cancer in high-risk populations. Improvements in specificity would improve its cost-effectiveness, as well as reduce anxiety associated with false positive tests. Samples from 235 patients with newly diagnosed lung cancer and matched controls were measured for the presence of AAbs to a panel of six (p53, NY-ESO-1, CAGE, GBU4-5, Annexin I, and SOX2) or seven (p53, NY-ESO-1, CAGE, GBU4-5, SOX2, HuD, and MAGE A4) antigens. Data were assessed in relation to cancer type and stage. The sensitivity and specificity of these two panels were also compared in two prospective consecutive series of 776 and 836 individuals at an increased risk of developing lung cancer. The six-AAb panel gave a sensitivity of 39 % with a specificity of 89 %, while the seven-AAb panel gave a sensitivity of 41 % with a specificity of 91 % which, once adjusted for occult cancers in the population, resulted in a specificity of 93 %. Analysis of these AAb assays in the at-risk population confirmed that the seven-AAb panel resulted in a significant increase in the specificity of the test from 82 to 90 %, with no significant change in sensitivity. The change from a six- to a seven-AAb assay can improve the specificity of the test and would result in a PPV of 1 in 8 and an overall accuracy of 92 %.

Identification of an autoantibody panel to separate lung cancer from smokers and nonsmokers

Background

Sera from lung cancer patients contain autoantibodies that react with tumor associated antigens (TAAs) that reflect genetic over-expression, mutation, or other anomalies of cell cycle, growth, signaling, and metabolism pathways.

Methods

We performed immunoassays to detect autoantibodies to ten tumor associated antigens (TAAs) selected on the basis of previous studies showing that they had preferential specificity for certain cancers. Sera examined were from lung cancer patients (22); smokers with ground-glass opacities (GGOs) (46), benign solid nodules (55), or normal CTs (35); and normal non-smokers (36). Logistic regression models based on the antibody biomarker levels among the high risk and lung cancer groups were developed to identify the combinations of biomarkers that predict lung cancer in these cohorts.

Results

Statistically significant differences in the distributions of each of the biomarkers were identified among all five groups. Using Receiver Operating Characteristic (ROC) curves based on age, c-myc, Cyclin A, Cyclin B1, Cyclin D1, CDK2, and survivin, we obtained a sensitivity = 81% and specificity = 97% for the classification of cancer vs smokers(no nodules, solid nodules, or GGO) and correctly predicted 31/36 healthy controls as noncancer.

Conclusion

A pattern of autoantibody reactivity to TAAs may distinguish patients with lung cancer versus smokers with normal CTs, stable solid nodules, ground glass opacities, or normal healthy never smokers.

Improving seroreactivity-based detection of glioma

Seroreactivity profiling emerges as valuable technique for minimal invasive cancer detection. Recently, we provided first evidence for the applicability of serum profiling of glioma using a limited number of immunogenic antigens. Here, we screened 57 glioma and 60 healthy sera for autoantibodies against 1827 Escherichia coli expressed clones, including 509 in-frame peptide sequences. By a linear support vector machine approach, we calculated mean specificity, sensitivity, and accuracy of 100 repetitive classifications. We were able to differentiate glioma sera from sera of the healthy controls with a specificity of 90.28%, a sensitivity of 87.31% and an accuracy of 88.84%. We were also able to differentiate World Health Organization grade IV glioma sera from healthy sera with a specificity of 98.45%, a sensitivity of 80.93%, and an accuracy of 92.88%. To rank the antigens according to their information content, we computed the area under the receiver operator characteristic curve value for each clone. Altogether, we found 46 immunogenic clones including 16 in-frame clones that were informative for the classification of glioma sera versus healthy sera. For the separation of glioblastoma versus healthy sera, we found 91 informative clones including 26 in-frame clones. The best-suited in-frame clone for the classification glioma sera versus healthy sera corresponded to the vimentin gene (VIM) that was previously associated with glioma. In the future, autoantibody signatures in glioma not only may prove useful for diagnosis but also offer the prospect for a personalized immune-based therapy.

Identification of lung cancer with high sensitivity and specificity by blood testing

Background

Lung cancer is a very frequent and lethal tumor with an identifiable risk population. Cytological analysis and chest X-ray failed to reduce mortality, and CT screenings are still controversially discussed. Recent studies provided first evidence for the potential usefulness of autoantigens as markers for lung cancer.

Methods

We used extended panels of arrayed antigens and determined autoantibody signatures of sera from patients with different kinds of lung cancer, different common non-tumor lung pathologies, and controls without any lung disease by a newly developed computer aided image analysis procedure. The resulting signatures were classified using linear kernel Support Vector Machines and 10-fold cross-validation.

Results

The novel approach allowed for discriminating lung cancer patients from controls without any lung disease with a specificity of 97.0%, a sensitivity of 97.9%, and an accuracy of 97.6%. The classification of stage IA/IB tumors and controls yielded a specificity of 97.6%, a sensitivity of 75.9%, and an accuracy of 92.9%. The discrimination of lung cancer patients from patients with non-tumor lung pathologies reached an accuracy of 88.5%.

Conclusion

We were able to separate lung cancer patients from subjects without any lung disease with high accuracy. Furthermore, lung cancer patients could be seprated from patients with other non-tumor lung diseases. These results provide clear evidence that blood-based tests open new avenues for the early diagnosis of lung cancer.

Tumor-Associated Antigens and Biomarkers in Cancer and Immune Therapy

Cancer has currently overtaken heart disease as the major cause of mortality in the United States. The Human Genome Project, advances in informatics, miniaturization of sample collection, and increased knowledge of cell signaling pathways has revolutionized the study of disease. Genomics, proteomics, and metabolomics are currently being used to develop molecular signatures for disease diagnosis, prognosis, and therapeutic efficacy. Tumor-associated antigens discovered by these methods are being used to develop passive (humoral) as well as active immunotherapy strategies to stimulate the immune system. Development and validation of biomarkers on a parallel track with therapeutics can speed development times by accurate screening of patient populations and substituting surrogate markers that correlate well with clinical outcomes.

Profiling tumor-associated autoantibodies for the detection of colon cancer

PURPOSE

The purpose of the present study was to screen the autoantibody signature of colon cancers to develop serum markers for colon cancer detection.

EXPERIMENTAL DESIGN

A phage cDNA expression library of colon cancer was built. The library was sequentially screened by a pool of 10 colon cancer sera, goat antihuman IgG, and a pool of two healthy sera to identify phage-expressed antigens recognized by tumor-associated antibodies. The clones picked out by these screening were subjected to a training set with 24 colon cancer sera and 24 healthy sera. The antigen combination, which got the most satisfactory classification, was tested by an independent set of 24 colon cancer sera with equal number of sera from normal donors. The carcinoembryonic antigen (CEA) level of these sera was detected for the additional classification analysis with or without the antigen combination.

RESULTS

A cDNA expression library consisting of 2 x 10(6) primary clones was prepared. After three turns of screening, 24 antigens recognized by tumor-associated antibodies were picked out for serum marker identification. The training set showed that a six-marker combination got the most satisfactory classification in a logistic regression model; leave-one-out validation achieved 91.7% sensitivity and 91.7% specificity. In a testing set with this marker panel, we correctly predicted 85% of the samples. Although according to CEA level alone, we correctly predicted 75% of the samples with 42% of cancer patients misclassified. When CEA was combined with the six markers, the sensitivity and specificity increased to 91.7% and 95.8%, respectively. The six antigen sequences in the phage display system are relatively short peptides. Only two of them showed homology to known protein sequences.

CONCLUSIONS

Autoantibodies against phage-expressed antigens derived from colon cancer tissues could be used as serum markers for the detection of colon cancer.

Autoantibodies as potential biomarkers for breast cancer

INTRODUCTION

Only a limited number of tumor markers for breast cancer are currently available. Antibodies to tumor-associated proteins may expand the number of available tumor markers for breast cancer and may be used together in a serum profile to enhance sensitivity and specificity.

METHODS

In the present study, we interrogated a breast cancer cDNA T7 phage library for tumor-associated proteins using biopan enrichment techniques with sera from normal individuals and from breast cancer patients. The enrichment of tumor-associated proteins after biopanning was tested using a plaque-lift assay and immunochemical detection. The putative tumor-associated phage clones were collected for PCR and sequencing analysis. Unique and open reading frame phage-expressed proteins were then used to develop phage protein ELISAs to measure corresponding autoantibodies using 87 breast cancer patients and 87 normal serum samples. A logistic regression model and leave-one-out validation were used to evaluate predictive accuracies with a single marker as well as with combined markers. Identities of those selected proteins were revealed through the sequence BLAST program.

RESULTS

We harvested 100 putative tumor-associated phage clones after biopan enrichment. Sequencing analysis revealed that six phage proteins were inframe and unique. Antibodies to these six phage-expressed proteins were measured by ELISAs, and the results showed that three of the phage clones had statistical significance in discriminating patients from normal individuals. BLAST results of the three proteins showed great matches to ASB-9, SERAC1, and RELT. Measurements of the three predictive phage proteins were combined in a logistic regression model that achieved 80% sensitivity and 100% specificity in prediction of sample status, whereas leave-one-out validation achieved 77.0% sensitivity and 82.8% specificity among 87 patient samples and 87 control samples. Receiver operating characteristic curve analysis and the leave-one-out method both showed that combined measurements of the three antibodies were more predictive of disease than any of the single antibodies studied, underscoring the importance of identifying multiple potential markers.

CONCLUSION

Serum autoantibody profiling is a promising approach for early detection and diagnosis of breast cancer. Rather than one autoantibody, a panel of autoantibodies appears preferable to achieve superior accuracy. Further refinements will need to be made to further improve the accuracy. Once refined, the assay must be applied to a prospective patient population to demonstrate applicability.

Panel of Serum Biomarkers for the Diagnosis of Lung Cancer

Purpose

Currently, a blood test for lung cancer does not exist. Serum biomarkers that could aid clinicians in making case management decisions would be enormously valuable. We used two proteomic platforms and a literature search to select candidate serum markers for the diagnosis of lung cancer.

Methods

We initially assayed six serum proteins, four discovered by proteomics and two previously known to be cancer associated, on a training set of sera from 100 patients (50 with a new diagnosis of lung cancer and 50 age- and sex-matched controls). Classification and Regression Tree (CART) analysis selected a panel of four markers that most efficiently predicted which patients had lung cancer. An independent, blinded validation set of sera from 97 patients (49 lung cancer patients and 48 matched controls) determined the accuracy of the four markers to predict which patients had lung cancer.

Results

Four serum proteins—carcinoembryonic antigen, retinol binding protein, α1-antitrypsin, and squamous cell carcinoma antigen—were collectively found to correctly classify the majority of lung cancer and control patients in the training set (sensitivity, 89.3%; specificity, 84.7%). These markers also accurately classified patients in the independent validation set (sensitivity, 77.8%; specificity, 75.4%). Remarkably, 90% of patients who fell into any one of three groupings in the CART analysis had lung cancer.

Conclusion

This panel of four serum proteins is valuable in suggesting the diagnosis of lung cancer. These data may be useful for treating patients with an indeterminate pulmonary lesion, and potentially in predicting individuals at high risk for lung cancer.

Autoantibody microarrays for biomarker discovery

Identification of autoantigens and the detection of autoantibody reactivity are useful in biomarker discovery and for explaining the role of important biochemical pathways in disease. Despite all of their potential advantages, the main challenge to working with autoantibodies is their sensitivity. Nevertheless, proteomics may hold the key to overcoming this limitation by providing the means to multiplex. Clearly, the ability to detect multiple autoantigens using a platform such as a high-density antigen microarray would improve sensitivity and specificity of detection for autoantibody profiling. The aims of this review are to: briefly describe the current status of antigen-autoantibody microarrays; provide examples of their use in biomarker discoveries; address current limitations; and provide examples and strategies to facilitate their implementation in the clinical setting.