Autoantibodies in lung cancer: possibilities for early detection and subsequent cure

Identification of biomarkers for the early detection of non-small cell lung cancer: a systematic review and meta-analysis

Lung cancer (LC) causes few symptoms in the earliest stages, leading to one of the highest mortality rates among cancers. Low-dose computerised tomography (LDCT) is used to screen high-risk individuals, reducing the mortality rate by 20%. However, LDCT results in a high number of false positives and is associated with unnecessary follow-up and cost. Biomarkers with high sensitivities and specificities could assist in the early detection of LC, especially in patients with high-risk features. Carcinoembryonic antigen (CEA), cytokeratin 19 fragments and cancer antigen 125 have been found to be highly expressed during the later stages of LC but have low sensitivity in the earliest stages. We determined the best biomarkers for the early diagnosis of LC, using a systematic review of eight databases. We identified 98 articles that focussed on the identification and assessment of diagnostic biomarkers and achieved a pooled area under curve of 0.85 (95% CI 0.82-0.088), indicating that the diagnostic performance of these biomarkers when combined was excellent. Of the studies, 30 focussed on single/antigen panels, 22 on autoantibodies, 31 on miRNA and RNA panels, and 15 suggested the use of circulating DNA combined with CEA or neuron-specific enolase (NSE) for early LC detection. Verification of blood biomarkers with high sensitivities (Ciz1, exoGCC2, ITGA2B), high specificities (CYFR21-1, antiHE4, OPNV) or both (HSP90α, CEA) along with miR-15b and miR-27b/miR-21 from sputum may improve early LC detection. Further assessment is needed using appropriate sample sizes, control groups that include patients with non-malignant conditions, and standardised cut-off levels for each biomarker.

The Usefulness of the Ratio of Antigen-Autoantibody Immune Complexes to Their Free Antigens in the Diagnosis of Non-Small Cell Lung Cancer

Autoantibodies against specific lung cancer-associated antigens have been suggested for the performance of lung cancer diagnosis. This study aimed to evaluate the diagnostic performance of the antigen-autoantibody immune complex (AIC) against its free antigens for CYFRA21-1, ProGRP, neutrophil gelatinase-associated lipocalin (NGAL), and neuron-specific enolase (NSE) in non-small cell lung cancer (NSCLC). In total, 85 patients with NSCLC and 120 healthy controls (HCs) were examined using a 9-guanine DNA chip method. The ratios of AICs to their antigens and the combinations of ratios consisting of two to four markers were calculated. The levels of AICs for CYFRA21-1, ProGRP, NGAL, and NSE were higher than those for their free antigens in all participants. The levels of each free antigens distinguished patients with NSCLC from the HCs. The ratios of the AIC to its antigen and seven combinations of two to four ratios were significantly higher in patients with NSCLC than in the HCs. Excellent diagnostic performance was observed for all combination ratios (C4-1), with 85.9% sensitivity and 86.7% specificity at a 3.51 cut-off. Higher sensitivity was observed in the early stages (0-I) and adenocarcinoma than in stages II-IV and other pathological types. Combining all ratios of AICs and their antigens for all four markers was useful when diagnosing NSCLC.

Novel Screening Tools for Lung Cancer

Screening with low-dose computed tomography has been shown to decrease lung cancer mortality. However, the issues of low detection rates and false positive results remain, highlighting the need for adjunctive tools in lung cancer screening. To this end, researchers have investigated easily applicable, minimally invasive tests with high validity. We herein review some of the more promising novel markers utilizing plasma, sputum, and airway samples.

Early detection of lung cancer in a real-world cohort via tumor-associated immune autoantibody and imaging combination

Background

Efficient early detection methods for lung cancer can significantly decrease patient mortality. One promising approach is the use of tumor-associated autoantibodies (TAABs) as a diagnostic tool. In this study, the researchers aimed to evaluate the potential of seven TAABs in detecting lung cancer within a population undergoing routine health examinations. The results of this study could provide valuable insights into the utility of TAABs for lung cancer screening and diagnosis.

Methods

In this study, the serum concentrations of specific antibodies were measured using enzyme-linked immunosorbent assay (ELISA) in a cohort of 15,430 subjects. The efficacy of both a 7-TAAB panel and LDCT for lung cancer detection were evaluated through receiver operating characteristic (ROC) analyses, with sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) being assessed and compared. These results could have significant implications for the development of improved screening methods for lung cancer.

Results

Over the 12-month observation period, 26 individuals were diagnosed with lung cancer. The 7-TAAB panel demonstrated promising sensitivity (61.5%) and a high degree of specificity (88.5%). The panel’s area under the receiver operating characteristic (ROC) curve was 0.8062, which was superior to that of any individual TAAB. In stage I patients, the sensitivity of the panel was 50%. In our cohort, there was no gender or age bias observed. This 7-TAAB panel showed a sensitivity of approximately 60% in detecting lung cancer, regardless of histological subtype or lesion size. Notably, ground-glass nodules had a higher diagnostic rate than solid nodules (83.3% vs. 36.4%, P = 0.021). The ROC analyses further revealed that the combination of LDCT with the 7-TAAB assay exhibited a significantly superior diagnostic efficacy than LDCT alone.

Conclusion

In the context of the study, it was demonstrated that the 7-TAAB panel showed improved detective efficacy of LDCT, thus serving as an effective aid for the detection of lung cancer in real-world scenarios.

Clinical significance of serum autoantibodies in patients with sarcoidosis

BACKGROUND

The association between sarcoidosis and autoimmunity has been reported for years. However, the significance of autoantibodies in the pathophysiology and clinical management of sarcoidosis is not well understood. No autoantibodies that can be used as serologic biomarkers to diagnose the disease, monitor the state of the disease, and predict the prognosis of patients are established.

METHODS

We performed a comprehensive analysis of serum autoantibodies and analyzed their associations with clinical features of sarcoidosis.

RESULTS

Patients with systemic autoimmune rheumatic diseases-associated autoantibodies had a higher prevalence of advanced radiographic stage and consolidations in high-resolution computed tomography than patients without autoantibodies (p < .05). Age, sex, clinical history, pulmonary function tests, serum angiotensin-converting enzyme levels, rheumatoid factor, and the number of involved organs were not significantly different between the two groups.

CONCLUSIONS

There may be an association between autoantibodies and more advanced pulmonary lesions in patients with sarcoidosis. Further investigations are needed to establish the significance of autoantibodies.

EarlyCDT Lung blood test for risk classification of solid pulmonary nodules: systematic review and economic evaluation

BACKGROUND

EarlyCDT Lung (Oncimmune Holdings plc, Nottingham, UK) is a blood test to assess malignancy risk in people with solid pulmonary nodules. It measures the presence of seven lung cancer-associated autoantibodies. Elevated levels of these autoantibodies may indicate malignant disease. The results of the test might be used to modify the risk of malignancy estimated by existing risk calculators, including the Brock and Herder models.

OBJECTIVES

The objectives were to determine the diagnostic accuracy, clinical effectiveness and cost-effectiveness of EarlyCDT Lung; and to develop a conceptual model and identify evidence requirements for a robust cost-effectiveness analysis.

DATA SOURCES

MEDLINE (including Epub Ahead of Print, In-Process & Other Non-Indexed Citations, Ovid MEDLINE Daily and Ovid MEDLINE), EMBASE, Cochrane Central Register of Controlled Trials, Science Citation Index, EconLit, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, Health Technology Assessment database, NHS Economic Evaluation Database ( NHS EED ) and the international Health Technology Assessment database were searched on 8 March 2021.

REVIEW METHODS

A systematic review was performed of evidence on EarlyCDT Lung, including diagnostic accuracy, clinical effectiveness and cost-effectiveness. Study quality was assessed with the quality assessment of diagnostic accuracy studies-2 tool. Evidence on other components of the pulmonary nodule diagnostic pathway (computerised tomography surveillance, Brock risk, Herder risk, positron emission tomography-computerised tomography and biopsy) was also reviewed. When feasible, bivariate meta-analyses of diagnostic accuracy were performed. Clinical outcomes were synthesised narratively. A simulation study investigated the clinical impact of using EarlyCDT Lung. Additional reviews of cost-effectiveness studies evaluated (1) other diagnostic strategies for lung cancer and (2) screening approaches for lung cancer. A conceptual model was developed.

RESULTS

A total of 47 clinical publications on EarlyCDT Lung were identified, but only five cohorts (695 patients) reported diagnostic accuracy data on patients with pulmonary nodules. All cohorts were small or at high risk of bias. EarlyCDT Lung on its own was found to have poor diagnostic accuracy, with a summary sensitivity of 20.2% (95% confidence interval 10.5% to 35.5%) and specificity of 92.2% (95% confidence interval 86.2% to 95.8%). This sensitivity was substantially lower than that estimated by the manufacturer (41.3%). No evidence on the clinical impact of EarlyCDT Lung was identified. The simulation study suggested that EarlyCDT Lung might potentially have some benefit when considering intermediate risk nodules (10-70% risk) after Herder risk analysis. Two cost-effectiveness studies on EarlyCDT Lung for pulmonary nodules were identified; none was considered suitable to inform the current decision problem. The conceptualisation process identified three core components for a future cost-effectiveness assessment of EarlyCDT Lung: (1) the features of the subpopulations and relevant heterogeneity, (2) the way EarlyCDT Lung test results affect subsequent clinical management decisions and (3) how changes in these decisions can affect outcomes. All reviewed studies linked earlier diagnosis to stage progression and stage shift to final outcomes, but evidence on these components was sparse.

LIMITATIONS

The evidence on EarlyCDT Lung among patients with pulmonary nodules was very limited, preventing meta-analyses and economic analyses.

CONCLUSIONS

The evidence on EarlyCDT Lung among patients with pulmonary nodules is insufficient to draw any firm conclusions as to its diagnostic accuracy or clinical or economic value.

FUTURE WORK

Prospective cohort studies, in which EarlyCDT Lung is used among patients with identified pulmonary nodules, are required to support a future assessment of the clinical and economic value of this test. Studies should investigate the diagnostic accuracy and clinical impact of EarlyCDT Lung in combination with Brock and Herder risk assessments. A well-designed cost-effectiveness study is also required, integrating emerging relevant evidence with the recommendations in this report.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42021242248.

FUNDING

This project was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 49. See the NIHR Journals Library website for further project information.

Antibodies as biomarkers for cancer risk: a systematic review

Increasing evidence has linked the humoral immune response with the development of various cancers. Therefore, there is growing interest in investigating the predictive value of antibodies to assess overall and tissue site-specific cancer risk. Given the large amount of antibody types and the broad scope of the search (i.e. cancer risk), the primary aim of this systematic review was to present an overview of the most researched antibodies (i.e. immunoglobulin (Ig) isotypes (IgG, IgM, IgA, and IgE), tumour and self-antigen-reactive antibodies, infection-related antibodies) in relation to overall and site-specific cancer risk. We identified various antibody types that have been associated with the risk of cancer. While no significant associations were found for IgM serum levels, studies found an inconsistent association among IgE, IgA, and IgG serum levels in relation to cancer risk. When evaluating antibodies against infectious agents, most studies reported a positive link with specific cancers known to be associated with the specific agent recognized by serum antibodies (i.e. helicobacter pylori and gastric cancer, hepatitis B virus and hepatocellular carcinoma, and human papillomavirus and cervical cancer). Several reports identified autoantibodies, as single biomarkers (e.g. anti-p53, anti-MUC1, and anti-CA125) but especially in panels of multiple autoantibodies, to have potential as diagnostic biomarkers for specific cancer types. Overall, there is emerging evidence associating certain antibodies to cancer risk, especially immunoglobulin isotypes, tumour-associated antigen-specific, and self-reactive antibodies. Further experimental studies are necessary to assess the efficacy of specific antibodies as markers for the early diagnosis of cancer.

Development of Diagnosis Model for Early Lung Nodules Based on a Seven Autoantibodies Panel and Imaging Features

Background

There is increasing incidence of pulmonary nodules due to the promotion and popularization of low-dose computed tomography (LDCT) screening for potential populations with suspected lung cancer. However, a high rate of false-positive and concern of radiation-related cancer risk of repeated CT scanning remains a major obstacle to its wide application. Here, we aimed to investigate the clinical value of a non-invasive and simple test, named the seven autoantibodies (7-AABs) assay (P53, PGP9.5, SOX2, GAGE7, GUB4-5, MAGEA1, and CAGE), in distinguishing malignant pulmonary diseases from benign ones in routine clinical practice, and construct a neural network diagnostic model with the development of machine learning methods.

Method

A total of 933 patients with lung diseases and 744 with lung nodules were identified. The serum levels of the 7-AABs were tested by an enzyme-linked Immunosorbent assay (ELISA). The primary goal was to assess the sensitivity and specificity of the 7-AABs panel in the detection of lung cancer. ROC curves were used to estimate the diagnosis potential of the 7-AABs in different groups. Next, we constructed a machine learning model based on the 7-AABs and imaging features to evaluate the diagnostic efficacy in lung nodules.

Results

The serum levels of all 7-AABs in the malignant lung diseases group were significantly higher than that in the benign group. The sensitivity and specificity of the 7-AABs panel test were 60.7% and 81.5% in the whole group, and 59.7% and 81.1% in cases with early lung nodules. Comparing to the 7-AABs panel test alone, the neural network model improved the AUC from 0.748 to 0.96 in patients with pulmonary nodules.

Conclusion

The 7-AABs panel may be a promising method for early detection of lung cancer, and we constructed a new diagnostic model with better efficiency to distinguish malignant lung nodules from benign nodules which could be used in clinical practice.

Rapid, site-specific labeling of "off-the-shelf" and native serum autoantibodies with T cell-redirecting domains

Extensive antibody engineering and cloning is typically required to generate new bispecific antibodies. Made-to-order genes, advanced expression systems, and high-efficiency cloning can simplify and accelerate this process, but it still can take months before a functional product is realized. We developed a simple method to site-specifically and covalently attach a T cell-redirecting domain to any off-the-shelf, human immunoglobulin G (IgG) or native IgG isolated from serum. No antibody engineering, cloning, or knowledge of the antibody sequence is required. Bispecific antibodies are generated in just hours. By labeling antibodies isolated from tumor-bearing mice, including two syngeneic models, we generated T cell-redirecting autoantibodies (TRAAbs) that act as an effective therapeutic. TRAAbs preferentially bind tumor tissue over healthy tissue, indicating a previously unexplored therapeutic window. The use of autoantibodies to direct the tumor targeting of bispecific antibodies represents a new paradigm in personalized medicine that eliminates the need to identify tumor biomarkers.

The role of autoantibody detection in the diagnosis and staging of lung cancer

Background

Previously, the clinical value of seven autoantibodies (p53, PGP9.5, SOX2, GAGE7, GBU4-5, MAGEA1, and CAGE) has been surveyed in our pilot observation and other published studies. Herein, we aimed to further investigate the role of these autoantibodies in the diagnosis and staging of LC.

Methods

We included a total of 135 individuals, who were divided into a Lung cancer (LC) group and a control group according to the final diagnosis. Seven autoantibody detection kits were used (ELISA method) for the expression measurement. The patients’ demographics information (e.g., age, gender, and smoking history) were also documented.

Results

Among the seven types of autoantibodies, only P53 and GBU4-5 were significantly increased in the LC group compared to the controls. Also, the P53 autoantibody was markedly different among the various subtype groups. Meanwhile, the GBU4-5 level was significantly higher in the small cell lung cancer (SCLC) patients compared to patients with adenocarcinoma (ADC). Autoantibodies against PGP9.5, SOX2, GBU4-5, and CAGE were found to be associated with stages. Their expressions were notably higher in the advanced stage (IV) versus early stages (I–II). Using logistic regression, the outcomes of LC prediction and stage prediction showed that the area under curve (AUCs) of the receiver operating characteristic (ROC) curves were 0.743 and 0.798, respectively.

Conclusions

In summary, our study confirmed the diagnostic value of tumor-associated autoantibodies, which may be useful as latent tumor markers to facilitate the detection of early LC. Single autoantibody testing is not yet sufficient in LC cancer screening, and the combined detection of autoantibodies can improve the sensitivity of detection compared with single antibody detection, especially for P53, PGP9.5, SOX2, GBU4-5, and CAGE autoantibodies.

LungNet: A hybrid deep-CNN model for lung cancer diagnosis using CT and wearable sensor-based medical IoT data

Lung cancer, also known as pulmonary cancer, is one of the deadliest cancers, but yet curable if detected at the early stage. At present, the ambiguous features of the lung cancer nodule make the computer-aided automatic diagnosis a challenging task. To alleviate this, we present LungNet, a novel hybrid deep-convolutional neural network-based model, trained with CT scan and wearable sensor-based medical IoT (MIoT) data. LungNet consists of a unique 22-layers Convolutional Neural Network (CNN), which combines latent features that are learned from CT scan images and MIoT data to enhance the diagnostic accuracy of the system. Operated from a centralized server, the network has been trained with a balanced dataset having 525,000 images that can classify lung cancer into five classes with high accuracy (96.81%) and low false positive rate (3.35%), outperforming similar CNN-based classifiers. Moreover, it classifies the stage-1 and stage-2 lung cancers into 1A, 1B, 2A and 2B sub-classes with 91.6% accuracy and false positive rate of 7.25%. High predictive capability accompanied with sub-stage classification renders LungNet as a promising prospect in developing CNN-based automatic lung cancer diagnosis systems.

Diagnostic, Predictive, and Prognostic Biomarkers in Non-Small Cell Lung Cancer (NSCLC) Management

Lung cancer is the leading cause of cancer-related deaths worldwide. Despite growing efforts for its early detection by screening populations at risk, the majority of lung cancer patients are still diagnosed in an advanced stage. The management of lung cancer has dramatically improved in the last decade and is no longer based on the "one-fits-all" paradigm or the general histological classification of non-small cell versus small cell lung cancer. Emerging options of targeted therapies and immunotherapies have shifted the management of lung cancer to a more personalized treatment approach, significantly influencing the clinical course and outcome of the disease. Molecular biomarkers have emerged as valuable tools in the prognosis and prediction of therapy response. In this review, we discuss the relevant biomarkers used in the clinical management of lung tumors, from diagnosis to prognosis. We also discuss promising new biomarkers, focusing on non-small cell lung cancer as the most abundant type of lung cancer.

Diagnostic value of serum tumor-associated autoantibodies in esophageal cancer

Aim: To explore the application value of serum autoantibodies in the early diagnosis of esophageal cancer. Materials & methods: A total of 130 patients with esophageal cancer and 110 controls were included and tested by ELISA. Results: According to the receiver operating characteristic curve, total sensitivity is 83.08%, total specificity is 72.73%. A nomogram was established based on the positive judgment standard, the area under the receiver operating characteristic curve was calculated to be 0.880 after verification with the calibration curve. A 2-week follow-up analysis found compared with the preoperative control, the postoperative model integral value will significantly decrease. Conclusion: The combination of serum autoantibody groups has certain clinical application value in the early diagnosis of esophageal cancer and can be used as an auxiliary index for early diagnosis.

Glycan-specific antibodies as potential cancer biomarkers: a focus on microarray applications

Glycosylation is one of the most common posttranslational modifications of proteins and lipids. In the case of tumors, cell transformation accompanied by aberrant glycosylation results in the expression of tumor-associated glycans that promote tumor invasion. As part of the innate immunity, anti-glycan antibodies recognize tumor-associated glycans, and these antibodies can be present in the bloodstream in the early stages of cancer. Recently, anti-glycan antibody profiles have been of interest in various cancer studies. Novel advantages in the field of analytical techniques have simplified the analysis of anti-glycan antibodies and made it easier to have more comprehensive knowledge about their functions. One of the robust approaches for studying anti-glycan antibodies engages in microarray technology. The analysis of glycan microarrays can provide more expanded information to simultaneously specify or suggest the role of antibodies to a wide variety of glycans in the progression of different diseases, therefore making it possible to identify new biomarkers for diagnosing cancer and/or the state of the disease. Thus, in this review, we discuss antibodies to various glycans, their application for diagnosing cancer and one of the most promising tools for the investigation of these molecules, microarrays.

The diagnostic efficiency of seven autoantibodies in lung cancer

This study aimed to evaluate the diagnostic efficacy of seven autoantibodies in all lung cancer, lung adenocarcinoma, lung squamous cell carcinoma and early-stage lung cancer patients. ELISA testing of a seven autoantibody panel was performed on 386 lung cancer patients and 238 normal controls. The sensitivity and specificity of each autoantibody were analyzed using the receiver operating characteristic curve analysis. The diagnostic efficacy of a combination of these seven autoantibodies was evaluated by binary logistic regression. The results indicated that six of the seven autoantibodies (p53, SOX2, GAGE7, GBU4-5, MAGEA1 and CAGE) had high specificity and low sensitivity, while PGP9.5 had high sensitivity and low specificity. Further analysis showed that all seven autoantibodies had better diagnostic value in lung squamous cell carcinoma patients when compared to lung adenocarcinoma or all lung cancer patients. Logistic regression showed that a combination of the seven autoantibodies resulted in more reliable detection of lung cancer than any individual autoantibody in early-stage lung cancer (sensitivity/specificity: 47.8%/81.4%, areas under the curve: 0.764, 95% confidence interval: 0.718-0.811). Additionally, this panel had a better sensitivity of 56.5% for detection of lung squamous cell carcinoma than for all lung cancer (50.1%) or adenocarcinoma (51.7%) (P < 0.05). Our results indicated that the seven autoantibody panel could be used for early lung cancer detection, and it had better sensitivity in diagnosis of lung squamous cell carcinoma.

Clinical value of tumor-associated antigens and autoantibody panel combination detection in the early diagnostic of lung cancer

BACKGROUND

This study aimed to investigate the efficiency of combining tumor-associated antigens (TAAs) and autoantibodies in the diagnosis of lung cancer.

METHODS

The serum levels of TAAs and seven autoantibodies (7-AABs) were detected from patients with lung cancer, benign lung disease and healthy controls. The performance of a new panel by combing TAAs and 7-AABs was evaluated for the early diagnosis of lung cancer.

RESULTS

The positive rate of 7-AABs was higher than the single detection of antibody. The positive rate of the combined detection of 7-AABs in lung cancer group (30.2%) was significantly higher than that of healthy controls (16.8%), but had no statistical difference compared with that of benign lung disease group (20.8%). The positive rate of 7-AABs showed a tendency to increase in lung cancer patients with higher tumor-node-metastasis (TNM) stages. For the pathological subtype analysis, the positive rate of 7-AABs was higher in patients with squamous cell carcinoma and small cell lung cancer than that of adenocarcinoma. The levels of carcinoembryonic antigen (CEA) and cytokeratin 19 fragment 211 (CYFRA 211) were significantly higher than that of benign lung disease and healthy control groups. An optimal model was established (including 7-AABs, CEA and CYFRA21-1) to distinguish lung cancer from control groups. The performance of this model was superior than that of single markers, with a sensitivity of 52.26% and specificity of 77.46% in the training group. Further assessment was studied in another validation group, with a sensitivity of 44.02% and specificity of 83%.

CONCLUSIONS

The diagnostic performance was enhanced by combining 7-AABs, CEA and CYFRA21-1, which has critical value for the screening and early detection of lung cancer.

Performance of the EarlyCDT® Lung test in detection of lung cancer and pulmonary metastases in a high-risk cohort

OBJECTIVES

Early detection of lung cancer is pivotal for an optimal prognosis. CT screening is currently implemented in USA. To decrease the amount of CT scans, the application of a blood-based biomarker as part of screening criteria is desirable.

MATERIALS AND METHODS

The EarlyCDT® Lung test was performed in a high-risk cohort composed 246 patients referred from their GP on suspicion of lung cancer. Blood samples were taken at first visit and patients underwent diagnostic workup on suspicion of lung cancer resulting in either a malignant diagnosis or ruled out cancer. Sensitivity and specificity of the EarlyCDT® Lung were calculated in the cohort and subgroups based on age, smoking history, sex and lung cancer stage.

RESULTS

Overall sensitivity in the cohort was 33 % for lung cancer and 31 % for primary lung cancer and lung metastases combined. Sensitivity in age groups was 11 % (60 years or below), 31 % (61-75 years) and 55 % (>75 years). In patients with at least 10 tobacco pack years, sensitivity was 33 % while the sensitivity in patients with at least 50 tobacco pack years was 44 %. The assay sensitivity in stage I-II lung cancer patients was 21 %, while this was 40 % in stage III-IV lung cancer patients. In a subgroup of patients that met current CT screening criteria (age 55-80 years and minimum 30 tobacco pack years) the sensitivity was 37 %.

CONCLUSION

The rationale of screening for lung cancer is to find patients in an early and resectable stage. However, the EarlyCDT® Lung test performed best in elderly, late stage lung cancer patients with a heavy smoking history. Based on these results, the current study finds insufficient sensitivity of the EarlyCDT® Lung test to be used as part of inclusion criteria in a low-dose CT program for detection of lung cancer.

Autoantibodies and cancer among asbestos-exposed cohorts in Western Australia

Asbestos exposure is associated with many adverse health conditions including malignant mesothelioma and lung cancer as well as production of autoantibodies. Autoantibodies may serve as biomarkers for asbestos exposure in patients with cancer, and autoimmune dysfunction has been linked to increased rates of various cancers. The aim of this study was to examine the hypothesis that autoantibodies are more frequent in asbestos-exposed individuals with either lung cancer or mesothelioma than those without these conditions. Asbestos-exposed individuals from Western Australia who had lung cancer (n = 24), malignant mesothelioma (n = 24), or no malignancy (n = 51) were tested for antinuclear autoantibodies (ANA) using indirect immunofluorescence and specific extractable nuclear autoantibodies (ENA) employing a multiplexed addressable laser bead immunoassay. Contrary to the hypothesis, data demonstrated that individuals without malignancy were more likely to be positive for ANA compared to those with cancer. However, autoantibodies to histone and Ro-60 were found to be associated with lung cancer. These results support a possible predictive value for specific autoantibodies in the early detection of lung cancer and/or in our understanding of the role of autoimmune processes in cancer. However, further studies are needed to identify specific target antigens for the antibodies.

The role of seven autoantibodies in lung cancer diagnosis

Background

To investigate the expression and diagnostic value of seven autoantibodies (P53, PGP9.5, SOX2, GAGE7, GBU4-5, MAGE, and CACE) in lung cancer patients.

Methods

A total of 370 patients were admitted to the Thoracic Surgery of the First Affiliated Hospital of Suzhou University from 2017 to 2019, including 305 patients with lung cancer and 65 patients with benign lesions. The concentrations of the seven autoantibodies were determined by enzyme linked immunosorbent assay (ELISA).The expression levels of each antibody were compared between the two groups, and the levels of each antibody between lung cancer patients with different pathological types were also compared. We aimed to analyze the diagnostic efficiency of single antibody detection combined with seven antibodies, and also to explore whether there were differences among the positive rates of each antibody in sex, age, smoking history, pathological classification, and clinical stages in the lung cancer group.

Results

The expression levels of seven autoantibodies in the lung cancer group were higher than those in the benign lesion group. In the lung cancer group, the expression levels of the seven autoantibodies did not vary statistically among different pathological types. The area under the curve of combined detection of the seven antibodies reached 0.735, and the Y-index reached 0.35, which was higher than that of single antibody detection. P53 exhibited the highest sensitivity and lowest specificity; meanwhile, PGP9.5, SOX2, GAGE7, GBU4-5, and MAGEA1 exhibited low sensitivity and high specificity. The sensitivity and specificity of the CAGE were approximately 60%, respectively. There was no statistical difference in the positive rate of each antibody in age, smoking history, and clinical stage. The positive rate of MAGEA1 and CAGE was statistically different in sex, and the positive rate of MAGEA1 was statistically different in pathological classification.

Conclusions

The seven autoantibodies of lung cancer can potentially be used as an auxiliary examination method for the early diagnosis of lung cancer.

The implication of autoantibodies in early diagnosis and monitoring of plasmonic photothermal therapy in the treatment of feline mammary carcinoma

Feline mammary carcinoma (FMC) shows great similarities to human breast cancer in the cellular and molecular levels. So, in cats as in humans, the role of immune responses is indicated to detect and follow up the development of tumors. As a new breast cancer therapeutic approach, Plasmonic Photothermal Therapy (PPTT) is an effective localized treatment for canine and feline mammary-carcinoma. Its systemic effect has not been inquired yet and needs many studies to hypothesis how the PPTT eradicates tumor cells. In this study, it is the first time to detect (P53, PCNA, MUC-1, and C-MYC) feline autoantibodies (AAbs), study the relationship between PCNA AAbs and mammary-tumors, and investigate the effect of PPTT on the humoral immune response of cats with mammary-carcinoma through detection of AAbs level before, during, and after the treatment. The four-AAbs panel was evaluated in serum of normal and clinically diagnosed cats with mammary tumors using Enzyme-Linked Immunosorbent Assay. The panel showed 100% specificity and 93.7% sensitivity to mammary tumors. The panel was evaluated in PPTT monotherapy, mastectomy monotherapy, and combination therapy. PPTT monotherapy decreased AAbs level significantly while mastectomy monotherapy and combination therapy had a nonsignificant effect on AAbs level.

The Value of a Seven-Autoantibody Panel Combined with the Mayo Model in the Differential Diagnosis of Pulmonary Nodules

Background

Identifying malignant pulmonary nodules and detecting early-stage lung cancer (LC) could reduce mortality. This study investigated the clinical value of a seven-autoantibody (7-AAB) panel in combination with the Mayo model for the early detection of LC and distinguishing benign from malignant pulmonary nodules (MPNs).

Methods

The concentrations of the elements of a 7-AAB panel were quantitated by enzyme-linked immunosorbent assay (ELISA) in 806 participants. The probability of MPNs was calculated using the Mayo predictive model. The performances of the 7-AAB panel and the Mayo model were analyzed by receiver operating characteristic (ROC) analyses, and the difference between groups was evaluated by chi-square tests (χ²).

Results

The combined area under the ROC curve (AUC) for all 7 AABs was higher than that of a single one. The sensitivities of the 7-AAB panel were 67.5% in the stage I-II LC patients and 60.3% in the stage III-IV patients, with a specificity of 89.6% for the healthy controls and 83.1% for benign lung disease patients. The detection rate of the 7-AAB panel in the early-stage LC patients was higher than that of traditional tumor markers. The AUC of the 7-AAB panel in combination with the Mayo model was higher than that of the 7-AAB panel alone or the Mayo model alone in distinguishing MPN from benign nodules. For early-stage MPN, the sensitivity and specificity of the combination were 93.5% and 58.0%, respectively. For advanced-stage MPN, the sensitivity and specificity of the combination were 91.4% and 72.8%, respectively. The combination of the 7-AAB panel with the Mayo model significantly improved the detection rate of MPN, but the positive predictive value (PPV) and the specificity were not improved when compared with either the 7-AAB panel alone or the Mayo model alone.

Conclusion

Our study confirmed the clinical value of the 7-AAB panel for the early detection of lung cancer and in combination with the Mayo model could be used to distinguish benign from malignant pulmonary nodules.

Can autoantibody tests enhance lung cancer screening?-an evaluation of EarlyCDT®-Lung in context of the German Lung Cancer Screening Intervention Trial (LUSI)

Background

Tumor-associated autoantibodies are considered promising markers for early lung cancer detection; so far, however, their capacity to detect cancer has been tested mostly in a clinical context, but not in population screening settings. This study evaluates the early detection accuracy, in terms of sensitivity and specificity, of EarlyCDT^®-Lung-a test panel of seven tumor-associated autoantibodies optimized for lung cancer detection-using blood samples originally collected as part of the German Lung Cancer Screening Intervention Trial.

Methods

The EarlyCDT^®-Lung test was performed for all participants with lung cancer detected via low-dose computed tomography and with available blood samples taken at detection, and for 180 retrospectively selected cancer-free participants at the end of follow-up: 90 randomly selected from among all cancer-free participants (baseline controls) and 90 randomly selected from among cancer-free participants with suspicious imaging findings (suspicious nodules controls). Sensitivity and specificity of lung cancer detection were estimated in the case group and the two control groups, respectively.

Results

In the case group, the test panel showed a sensitivity of only 13.0% (95% CI: 4.9-26.3%). Specificity was estimated at 88.9% (95% CI: 80.5-94.5%) in the baseline control group, and 91.1% (95% CI: 83.2-96.1%) among controls presenting CT-detected nodules.

Conclusions

The test panel showed insufficient sensitivity for detecting lung cancer at an equally early stage as with low-dose computed tomography screening.

Autoantibodies against tumor-associated antigens in sputum as biomarkers for lung cancer

Tumor antigens (TAs) can initiate host immune responses and produce TA-associated autoantibody (TAAbs), potential cancer biomarkers. Sputum is directly generated from the upper and lower airways, and thus can be used as a surrogate sample for the diagnosis of lung cancer based on molecular analysis. To develop sputum TAAb biomarkers for the early detection of lung cancer, the leading cause of cancer death, we probed a protein microarray containing more than 9,000 antigens with sputum supernatants of a discovery set of 30 lung cancer patients and 30 cancer-free smokers. Twenty-eight TAs with higher reactivity in sputum of lung cancer cases vs. controls were identified. The diagnostic significance of TAAbs against the TAs was determined by enzyme-linked immunosorbent assays (ELISAs) in sputum of the discovery set and additional 166 lung cancer patients and 213 cancer-free smokers (validation set). Three sputum TAAbs against DDX6, ENO1, and 14-3-3ζ were developed as a biomarker panel with 81% sensitivity and 83% specificity for diagnosis of lung cancer, regardless of stages, locations, and histological types of lung tumors. This study provides the first evidence that sputum TAAbs could be used as biomarkers for the early detection of lung cancer.

Autoantibody Formation and Mapping of Immunogenic Epitopes against Cold-Shock-Protein YB-1 in Cancer Patients and Healthy Controls

Simple Summary

Cold shock Y-box binding protein-1 plays a crucial role in cancerous cell transformation and proliferation. Experimental evidence links autoantibody formation with cancer diseases as well as YB 1 protein levels. Hence, we investigated autoantibody formation targeting YB-1 in cancer patients. Using recombinant proteins and specific peptide arrays, we mapped linear epitopes, which localize in the cold shock and C-terminal domain of the protein, in cancer patients that differ from healthy controls. Furthermore, cancer sera containing autoantibodies that target YB-1 extend the half-life of the YB-1 protein. Since extracellular YB-1 serves as a ligand for receptor Notch3 as well as TNFR1, this may contribute to aberrant signaling that promotes tumor development. In the clinical setting, we envision setting up detection assays for the immune response against YB-1, which may aid in screening for cancer.

Abstract

Cold shock Y-box binding protein-1 participates in cancer cell transformation and mediates invasive cell growth. It is unknown whether an autoimmune response against cancerous human YB-1 with posttranslational protein modifications or processing develops. We performed a systematic analysis for autoantibody formation directed against conformational and linear epitopes within the protein. Full-length and truncated recombinant proteins from prokaryotic and eukaryotic cells were generated. Characterization revealed a pattern of spontaneous protein cleavage, predominantly with the prokaryotic protein. Autoantibodies against prokaryotic, but not eukaryotic full-length and cleaved human YB-1 protein fragments were detected in both, healthy volunteers and cancer patients. A mapping of immunogenic epitopes performed with truncated E. coli-derived GST-hYB-1 proteins yielded distinct residues in the protein N- and C-terminus. A peptide array with consecutive overlapping 15mers revealed six distinct antigenic regions in cancer patients, however to a lesser extent in healthy controls. Finally, a protein cleavage assay was set up with recombinant pro- and eukaryotic-derived tagged hYB-1 proteins. A distinct cleavage pattern developed, that is retarded by sera from cancer patients. Taken together, a specific autoimmune response against hYB-1 protein develops in cancer patients with autoantibodies targeting linear epitopes.

Noninvasive Diagnostics for Early Detection of Lung Cancer: Challenges and Potential with a Focus on Changes in DNA Methylation

Lung cancer remains the leading cause of cancer deaths in the United States and the world. Early detection of this disease can reduce mortality, as demonstrated for low-dose computed tomography (LDCT) screening. However, there remains a need for improvements in lung cancer detection to complement LDCT screening and to increase adoption of screening. Molecular changes in the tumor, and the patient's response to the presence of the tumor, have been examined as potential biomarkers for diagnosing lung cancer. There are significant challenges to developing an effective biomarker with sufficient sensitivity and specificity for the early detection of lung cancer, particularly the detection of circulating tumor DNA, which is present in very small quantities. We will review approaches to develop biomarkers for the early detection of lung cancer, with special consideration to detection of rare tumor events, focus on the use of DNA methylation-based detection in plasma and sputum, and discuss the promise and challenges of lung cancer early detection. Plasma-based detection of lung cancer DNA methylation may provide a simple cost-effective method for the early detection of lung cancer.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

Autoantibodies to tumor-associated antigens in lung cancer diagnosis

Lung cancer (LC) accounts for the majority of cancer-related deaths worldwide. Although screening the high-risk population by low-dose CT (LDCT) has reduced mortality, the cost and high false positivity rate has prevented its general diagnostic use. As such, better and more specific minimally invasive biomarkers are needed in general and for early LC detection, specifically. Autoantibodies produced by humoral immune response to tumor-associated antigens (TAA) are emerging as a promising noninvasive biomarker for LC. Given the low sensitivity of any one single autoantibody, a panel approach could provide a more robust and promising strategy to detect early stage LC. In this review, we summarize the background of TAA autoantibodies (TAAb) and the techniques currently used for identifying TAA, as well as recent findings of LC specific antigens and TAAb. This review provides guidance toward the development of accurate and reliable TAAb as immunodiagnostic biomarkers in the early detection of LC.

Stem signatures associated antibodies yield early diagnosis and precise prognosis predication of patients with non-small cell lung cancer

BACKGROUND

This study was designed to detect patients with early NSCLC with tentatively using the stem signatures associated autoantibodies (AAbs), and to evaluate its latent values in the early diagnosis and precise prognosis prediction.

METHODS

The serum concentrations of selective antibodies were quantitated by enzyme-linked immunosorbent assay (ELISA), and a total of 458 cases were enrolled (training set = 401; validation set = 57). TCGA databases were used to analyze the distinct expressions and prognostic values of related genes. The optimal cut-off values were 11.60 U/ml for P53, 4.90 U/ml for MAGEA1, 3.85 U/ml for SOX2, and 7.05U/ml for PGP9.5.

RESULTS

We found that the stem signatures associated antibodies of MAGEA1, PGP9.5, SOX2, and TP53 exhibited high expressions in NSCLC, negatively correlating with the overall survival (OS) (P < 0.05). In the test groups, the diagnosis sensitivity of P53, PGP9.5, SOX2, and MAGEA1 reached to 21.5%, 39.0%, 50.3%, and 35.0%, respectively, and the specificity reached to 98.7%, 99.4%, 92.2%, and 97.4%. The four candidates' panel gave a sensitivity of 71.8% with a specificity of 89%. In the validation group, the detection of the four antibodies in early diagnosis of NSCLC also exhibited high specificity and sensitivity, further consolidating their potential application.

CONCLUSIONS

The detection regarding stem signatures associated antibodies could be used as effective tools in early NSCLC diagnosis, but not for localized screening of cancers, and their abnormal expression was in accordance with poorer survival.

Detection of circulating natural antibodies against CD25, MUC1, and VEGFR1 for early diagnosis of non-small cell lung cancer

We previously demonstrated that a deficiency of natural antibodies against CD25, Mucin 1 (MUC1), and vascular endothelial growth factor receptor 1 (VEGFR1) could contribute to high risk of non‐small cell lung cancer (NSCLC). This study was designed to investigate whether natural IgG antibodies against POU domain class 5 transcription factor 1 (POU5F1), tumor necrosis factor‐α (TNF‐α), and the combination of CD25, VEGFR1, and MUC1 could play an anti‐tumorigenic role against developing NSCLC. An ELISA was developed in‐house to examine plasma IgG against peptide antigens derived from POU5F1, TNF‐α, and a combination of peptide antigens derived from CD25, MUC1, and VEGFR1 in 211 patients with NSCLC and 200 healthy controls. Mann–Whitney U test demonstrated that plasma IgG levels for the combination of peptide antigens derived from CD25, MUC1, and VEGFR1 were significantly lower in NSCLC patients than control subjects (Z = −12.978, P < 0.001) although plasma levels of IgG antibodies for POU5F1 and TNFα were not significantly changed. The in‐house ELISA made with the CD25‐MUC1‐VEGFR1 combination had a sensitivity of 49.6% against a specificity of 95% to detect early‐stage NSCLC. In conclusion, natural antibodies against the combination of CD25, VEGFR1, and MUC1 may be an effective biomarker for early diagnosis of NSCLC.

M2 Macrophages Infiltrating Epithelial Ovarian Cancer Express MDR1: A Feature That May Account for the Poor Prognosis

Multi drug resistance protein 1 (MDR1) expression on tumor cells has been widely investigated in context of drug resistance. However, the role of MDR1 on the immune cell infiltrate of solid tumors remains unknown. The aim of this study was to analyze the prognostic significance of a MDR1+ immune cell infiltrate in epithelial ovarian cancer (EOC) and to identify the MDR1+ leucocyte subpopulation. MDR1 expression was analyzed by immunohistochemistry in 156 EOC samples. In addition to MDR1+ cancer cells, we detected a MDR1+ leucocyte infiltrate (high infiltrate >4 leucocytes per field of view). Correlations and survival analyses were calculated. To identify immune cell subpopulations immunofluorescence double staining was performed. The MDR1+ leucocyte infiltrate was associated with human epidermal growth factor receptor 2 (HER2) (cc = 0.258, p = 0.005) and tumor-associated mucin 1 (TA-MUC1) (cc = 0.202, p = 0.022) expression on cancer cells. A high MDR1+ leucocyte infiltrate was associated with impaired survival, especially in patients whose carcinoma showed either serous histology (median OS 28.80 vs. 50.64 months, p = 0.027, n = 91) or TA-MUC1 expression (median OS 30.60 vs. 63.36 months, p = 0.015, n = 110). Similar findings for PFS suggest an influence of MDR1+ immune cells on the development of chemoresistance. A Cox regression analysis confirmed the independency of a high MDR1+ leucocyte infiltrate as prognostic factor. M2 macrophages were identified as main part of the MDR1+ leucocyte infiltrate expressing MDR1 as well as the M2 marker CD163 and the pan-macrophage marker CD68. Infiltration of MDR1+ leucocytes, mostly M2 macrophages, is associated with poor prognosis of EOC patients. Further understanding of the interaction of M2 macrophages, MDR1 and TA-MUC1 appears to be a key aspect to overcome chemoresistance in ovarian cancer.

Autoantibodies as diagnostic biomarkers for lung cancer: A systematic review

Lung cancer (LC) accounts for the largest number of tumor-related deaths worldwide. As the overall 5-year survival rate of LC is associated with its stages at detection, development of a cost-effective and noninvasive cancer screening method is necessary. We conducted a systematic review to evaluate the diagnostic values of single and panel tumor-associated autoantibodies (TAAbs) in patients with LC. This review included 52 articles with 64 single TAAbs and 19 with 20 panels of TAAbs. Enzyme-linked immunosorbent assays (ELISA) were the most common detection method. The sensitivities of single TAAbs for all stages of LC ranged from 3.1% to 92.9% (mean: 45.2%, median: 37.1%), specificities from 60.6% to 100% (mean: 88.1%, median: 94.9%), and AUCs from 0.416 to 0.990 (mean: 0.764, median: 0.785). The single TAAb with the most significant diagnostic value was the autoantibody against human epididymis secretory protein (HE4) with the maximum sensitivity 91% for NSCLC. The sensitivities of the panel of TAAbs ranged from 30% to 94.8% (mean: 76.7%, median: 82%), specificities from 73% to 100% (mean: 86.8%, median: 89.0%), and AUCs from 0.630 to 0.982 (mean: 0.821, median: 0.820), and the most significant AUC value in a panel (M13 Phage 908, 3148, 1011, 3052, 1000) was 0.982. The single TAAb with the most significant diagnostic calue for early stage LC, was the autoantibody against Wilms tumor protein 1 (WT1) with the maximum sensitivity of 90.3% for NSCLC and its sensitivity and specificity in a panel (T7 Phage 72, 91, 96, 252, 286, 290) were both above 90.0%. Single or TAAbs panels may be useful biomarkers for detecting LC patients at all stages or an early-stage in high-risk populations or health people, but the TAAbs panels showed higher detection performance than single TAAbs. The diagnostic value of the panel of six TAAbs, which is higher than the panel of seven TAAbs, may be used as potential biomarkers for the early detection of LC and can probably be used in combination with low-dose CT in the clinic.

Five tumor-associated autoantibodies expression levels in serum predict lung cancer and associate with poor outcome

Background

This study aims to evaluate diagnostic feasibility of the tumor-associated autoantibodies and their clinical significance in lung cancer.

Methods

Blood samples were collected from 352 lung cancer patients and 226 healthy individuals. Immunohistochemical staining was used to evaluate the expression of autoantibodies in 69 cases of lung cancer tissues. Enzyme-linked immunosorbent assay (ELISA) was performed to measure the five autoantibodies levels in serum from lung cancer patients and healthy controls.

Results

Higher expression of GAGE7, MAGEA1, PGP9.5, CAGE and p53 were found in lung cancer tissues than normal tissues from the cancer genome atlas (TCGA) database. The expression levels of the five tumor-associated autoantibodies in lung cancer tissues were positively associated with those statuses in serum. There were significantly higher levels of each autoantibody in lung cancer patients than healthy individuals. The area under curve (AUC) for GAGE7, MAGEA1, PGP9.5, CAGE and p53 in diagnosis of lung cancer were 0.787, 0.641, 0.873, 0.825 and 0.749, respectively. With combination of these five autoantibodies by the logistic regression model, 0.891 of AUC was shown. In addition, the level of each autoantibody was increased in the advanced stage. Particularly, the level of PGP9.5 was significantly higher in the advanced T stage, N stage and TNM stage and CAGE was significantly elevated in the advanced N stage.

Conclusions

Summarily, autoantibodies levels of GAGE7, MAGEA1, PGP9.5, CAGE and p53 in serum could be used for the diagnosis of lung cancer and PGP9.5 may predict poor prognosis for the patients with lung cancer.

Enhancement of diagnostic performance in lung cancers by combining CEA and CA125 with autoantibodies detection

Objectives: Although low-dose computed tomography has been confirmed to have meaningful diagnostic utility, lung cancer is still the leading cause of cancer-related deaths for both genders worldwide. Thus, a novel panel with a stronger diagnostic performance for lung cancer is needed. This study aimed to investigate the efficacy of a new panel in lung cancer diagnosis.

Materials and Methods: The serum levels of carcinoembryonic antigen (CEA), cancer antigen 125 (CA125) and seven autoantibodies were measured and statistically analyzed in samples from healthy controls and patients with lung cancer. The 316 candidates enrolled in this study were randomly assigned into two groups for the training and validation of a diagnostic panel.

Results: An optimal panel with four biomarkers (CEA, CA125, Annexin A1-Ab, and Alpha enolase-Ab) was established, with an area under the receiver operator characteristic (ROC) curve (AUC) of 0.897, a sensitivity of 86.5%, a specificity of 82.3%, a positive predictive value (PPV) of 88.3%, a negative predictive value (NPV) of 79.7%, and a diagnostic accuracy of 84.8% for the training group. The panel was validated, with an AUC of 0.856 and a sensitivity of 87.5% for the validation group. Furthermore, the new panel performed significantly better in lung cancer screening than did CEA and CA125 in all of the cohorts (p< .05).

Conclusion: The diagnostic performance of CEA and CA125 was significantly enhanced through their combination with two autoantibodies (Annexin A1-Ab, and Alpha enolase-Ab). Optimization of the measured autoantibodies is critical for generating a panel to detect lung cancer in patients.

Establishing a detection method for CCNY: a potentially significant clinical investigative marker in NSCLC patients

Background

CCNY, a novel cyclin family member, plays an increasingly important role in the progression of tumor invasion and metastasis, including lung cancer. However, the clinical significance of CCNY in non-small-cell lung cancer (NSCLC) patients is unknown.

Patients and methods

We prepared CCNY monoclonal antibodies, validated specific peptides by a peptide array, and established a double-antibody sandwich ELISA detection method. Then, we measured CCNY levels in 100 NSCLC patients and 50 healthy controls. A blinded validation was subsequently performed in 399 NSCLC patients and 150 healthy controls.

Results

We successfully prepared two specific mouse anti-human CCNY monoclonal antibodies and established a reliable and stable detection method. In the training set, serum CCNY was markedly increased in the NSCLC patients (P<0.05) with an integrated area under the curve of 0.751. With further analysis of the CCNY levels, there were no differences in age, sex, smoking status, tumor location, histologic subtype, or tumor size, but differences were observed in lymphatic (P<0.001) and distant (P<0.001) metastases in NSCLC patients. The CCNY[+] patients had a shorter survival time and progression-free survival than CCNY[−] patients at 3-year follow-up (P<0.001). The results were confirmed by the validation set.

Conclusion

Our study suggests that CCNY may be useful as a latent tumor marker to facilitate diagnosis and may be an effective indicator of tumor aggressiveness, playing an important role in the prognosis of NSCLC patients.

Natural antibodies - facts known and unknown

In contrast to adaptive antibodies, natural antibodies are present in a non-immunised organism from birth, and they do not include anti-Gal antibodies and/or anti-Gal natural antibodies, which are developed as a result of the effect of the α-Gal epitope and physiological flora. Natural antibodies are the first line of the organism’s defence before the formation of the immunity created via the stimulation of elements that determine specific and non-specific immunity. This is especially important in the case of infants. Despite the fact that natural antibodies differ in their function from adaptive antibodies, they are polyreactive and they detect autoantigens and new antigenic determinants. Natural antibodies are formed from the subpopulation of B lymphocytes, mainly B1 lymphocytes and B lymphocytes of the marginal zone. This phenomenon is supported by the fact that when the quantity of these cells in the organism decreases, which happens with age, the level of natural antibodies also decreases and the risk of illnesses of old age becomes higher. During ontogenesis, these antibodies participate in many physiological processes, including the “support” of the immune system and homeostasis, the prevention of inflammation, infections and other pathological states, such as autoimmune and cardiovascular diseases, or the process of carcinogenesis. The best known natural antibody is IgM, but the role of IgGs and IgAs is also considered important. Nowadays, many researchers also mention intravenous immunoglobulins, which are used in the treatment of numerous illnesses, and there are discussions on the possibility of increasing their potential if they were based on natural antibodies.

Serum carbonic anhydrase I and II autoantibodies in patients with chronic lymphocytic leukaemia

Cancer is the second most important cause of mortality, and millions of people either have or have had the disease. Leukaemia is one of the most common forms of cancer. Autoantibodies that have developed against the organism’s self-antigens are detected in the sera of subjects with cancer. In recent years carbonic anhydrase (CA) autoantibodies have been determined in some autoimmune diseases and carcinomas, but the mechanisms underlying this immune response have not yet been fully explained. The purpose of this study was to determine CA I and II autoantibodies in subjects with chronic lymphocytic leukaemia (CLL) and to provide a novel perspective regarding the autoimmune basis of the disease. Autoantibody levels were investigated using enzyme-linked immunosorbent assay (ELISA) in serum samples from 37 patients with CLL and 37 healthy peers. Anti-CA I titres in the CLL group were significantly higher compared with the control group (p = 0.0001). However, there was no significant difference between CLL and control groups in terms of anti-CA II titres (p = 0.278). The prevalences of CA I and II autoantibodies in patients with CLL in this study were 27% and 24.3%, respectively. Our results suggest that these autoantibodies may be involved in the pathogenesis of CLL. More extensive studies are now needed to reveal the entire mechanism.

Circulating anti-p16a IgG autoantibodies as a potential prognostic biomarker for non-small cell lung cancer

It has been reported that p16 protein is overexpressed in many types of solid cancer and its aberrant expression may trigger the immune response, leading to the secretion of anti‐p16 antibodies. Here, we developed an in‐house ELISA with three p16‐derived linear peptide antigens to examine plasma anti‐p16 antibody levels in patients with non‐small cell lung cancer (NSCLC). Blood samples were taken from 200 control subjects and 211 patients with NSCLC prior to anticancer therapy. A Mann–Whitney U test demonstrated that plasma anti‐p16a IgG levels were significantly higher in NSCLC patients than in control subjects (Z = −11.14, P < 0.001). However, neither plasma anti‐p16b nor plasma anti‐p16c IgG levels showed significant differences in patients with NSCLC as compared to control subjects. Moreover, further analysis indicated that anti‐p16a IgG levels increased with tumor stages, and patients with late stage NSCLC, namely group IV, had the highest IgG levels among four subgroups. Receiver operating characteristic analysis revealed that the anti‐p16a IgG assay had a sensitivity of 32.7% against a specificity of 95.0% in group IV, while Kaplan–Meier survival analysis revealed no significant difference in overall survival between patients with high anti‐p16a IgG levels and those with low anti‐p16a IgG levels (χ² = 0.24, P = 0.63). In conclusion, anti‐p16a IgG may be suitable for use as a prognostic biomarker for NSCLC.

Alteration of circulating natural autoantibodies to CD25-derived peptide antigens and FOXP3 in non-small cell lung cancer

Natural autoantibody is a key component for immune surveillance function. Regulatory T (Treg) cells play indispensable roles in promoting tumorigenesis via immune escape mechanisms. Both CD25 and FOXP3 are specific markers for Treg cells and their natural autoantibodies may be involved in anticancer activities. This work was designed to develop an in-house enzyme-linked immunosorbent assay (ELISA) to examine plasma natural IgG against CD25 and FOXP3 in non-small cell lung cancer (NSCLC). Compared with control subjects, NSCLC patients had significantly higher levels of plasma IgG for CD25a (Z = -8.05, P < 0.001) and FOXP3 (Z = -4.17, P < 0.001), lower levels for CD25b (Z = -3.58, P < 0.001), and a trend toward lower levels for CD25c (Z = -1.70, P = 0.09). Interestingly, the anti-CD25b IgG assay had a sensitivity of 25.0% against a specificity of 95.0% in an early stage patients (T1N0M0) who showed the lowest anti-CD25b IgG levels among 4 subgroups classified based on staging information. Kaplan-Meier survival analysis showed that patients with high anti-FOXP3 IgG levels had shorter survival than those with low anti-FOXP3 IgG levels (χ2 = 3.75, P = 0.05). In conclusion, anti-CD25b IgG may be a promising biomarker in terms of screening individuals at high risk of lung cancer.

Developments in Point-of-Care Diagnostic Technology for Cancer Detection

Cancer is the cause of death for one in seven individuals worldwide. It is widely acknowledged that screening and early diagnosis are of vital importance for improving the likelihood of recovery. However, given the costly, time-consuming, and invasive nature of the many methods currently in use, patients often do not take advantage of the services available to them. Consequently, many researchers are exploring the possibility of developing fast, reliable, and non-invasive diagnostic tools that can be used directly or by local physicians at the point-of-care. Herein, we look at the use of established biomarkers in cancer therapy and investigate emerging biomarkers exhibiting future potential. The incorporation of these biomarkers into point-of-care devices could potentially reduce the strain currently experienced by screening programs in hospitals and healthcare systems. Results derived from point-of-care tests should be accurate, sensitive, and generated rapidly to assist in the selection of the best course of treatment for optimal patient care. Essentially, point-of-care diagnostics should enhance the well-being of patients and lead to a reduction in cancer-related deaths.

Liquid biopsy for early stage lung cancer

Liquid biopsy, which analyzes biological fluids especially blood specimen to detect and quantify circulating cancer biomarkers, have been rapidly introduced and represents a promising potency in clinical practice of lung cancer diagnosis and prognosis. Unlike conventional tissue biopsy, liquid biopsy is non-invasive, safe, simple in procedure, and is not influenced by manipulators' skills. Notably, some circulating cancer biomarkers are already detectable in disease with low-burden, making liquid biopsy feasible in detecting early stage lung cancer. In this review, we described a landscape of different liquid biopsy methods by highlighting the rationale and advantages, accessing the value of various circulating biomarkers and discussing their possible future development in the detection of early lung cancer.

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.

Use of autoantibodies against tumor-associated antigens as serum biomarkers for primary screening of cervical cancer

Serum autoantibodies against tumor-associated antigens (TAAs) have received much attention as potential biomarkers for early detection of cancers, since they can be detected in the early stages of cancers. Autoantibodies against Cancer Antigen 15-3 (CA15-3), carcinoembryonic antigen (CEA), Cancer Antigen 19-9 (CA19-9), c-Myc, p53, heat shock protein (Hsp)27 and Hsp70 have been suggested as potential markers for detecting several types of cancer. In the present study, the seven types of antibody listed above were evaluated for detecting cervical lesions. Enzyme-linked immunosorbent assays (ELISAs) were used to measure IgG levels of the autoantibodies in women with normal cytology, cervical intraepithelial neoplasia (CIN) I, CIN II, CIN III and cervical cancer. The increases of anti-CA15-3 and anti-CEA IgG in cervical cancer were more pronounced than the increases of the other markers, and the level of anti-CA19-9 IgG in CIN III stage was higher than in normal CIN I, CIN II or cervical cancer. A combination of ELISAs detecting anti-CA15-3, anti-CEA and anti-CA19-9 IgGs was found to reliably discriminate CINs from normal and to strongly differentiate cancer from normal (90.3% of sensitivity and 82.1% of specificity). We suggest that the combination of three ELISA may be useful for detecting cervical lesions.

Comparative Network Analysis of Patients with Non-Small Cell Lung Cancer and Smokers for Representing Potential Therapeutic Targets

Cigarette smoking is the leading cause of lung cancer worldwide. In this study, we evaluated the serum autoantibody (AAb) repertoires of non-small cell lung cancer (NSCLC) patients and smokers (SM), leading to the identification of overactivated pathways and hubs involved in the pathogenesis of NSCLC. Surface- and solution-phase biopanning were performed on immunoglobulin G purified from the sera of NSCLC and SM groups. In total, 20 NSCLC- and 12 SM-specific peptides were detected, which were used to generate NSCLC and SM protein datasets. NSCLC- and SM-related proteins were visualized using STRING and Gephi, and their modules were analyzed using Enrichr. By integrating the overrepresented pathways such as pathways in cancer, epithelial growth factor receptor, c-Met, interleukin-4 (IL-4) and IL-6 signaling pathways, along with a set of proteins (e.g. phospholipase D (PLD), IL-4 receptor, IL-17 receptor, laminins, collagens, and mucins) into the PLD pathway and inflammatory cytokines network as the most critical events in both groups, two super networks were made to elucidate new aspects of NSCLC pathogenesis and to determine the influence of cigarette smoking on tumour formation. Taken together, assessment of the AAb repertoires using a systems biology approach can delineate the hidden events involved in various disorders.

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.