Autoantibodies against tumor-associated antigens in the early detection of lung cancer

An analysis of the influencing factors of false negative autoantibodies in patients with non-small cell lung cancer

Objectives

To analyze the clinical significance of seven autoantibodies (P53, PGP9.5, SOX2, GAGE7, GBU4-5, MAGE, and CAGE) in patients with non-small cell lung cancer (NSCLC) and the factors that influence false-negative results.

Methods

Seven autoantibodies were measured in the serum of 502 patients with non-small cell lung cancer (NSCLC) using ELISA, and their correlations with age, sex, smoking history, pathological type, clinical stage, and PD-L1 gene expression were analyzed. The clinicopathological data of the false-negative and positive groups for the seven autoantibodies were compared to determine the influencing factors.

Results

P53 antibody expression level was correlated with lobulation sign, PGP9.5 antibody expression level with sex and vascular convergence; SOX2 antibody expression level with pathological type, clinical stage, and enlarged lymph nodes; and MAGE antibody expression level with the pathological type (P<0.05). False-negative autoantibodies are prone to occur in lung cancer patients with ground-glass nodules, no enlarged lymph nodes, no vascular convergence, and PD-L1 gene expression <1% (P <0.05).

Conclusion

Detection of seven autoantibodies was clinically significant in patients with NSCLC. However, poor sensitivity should be considered in clinical diagnoses to prevent missed diagnoses.

Combination of an Autoantibody Panel and Alpha-Fetoprotein for Early Detection of Hepatitis B Virus-Associated Hepatocellular Carcinoma

The purpose of this study was to identify biomarkers associated with hepatitis B virus-associated hepatocellular carcinoma (HBV-HCC) and to develop a new combination with good diagnostic performance. This study was divided into four phases: discovery, verification, validation, and modeling. A total of four candidate tumor-associated autoantibodies (TAAb; anti-ZIC2, anti-PCNA, anti-CDC37L1, and anti-DUSP6) were identified by human proteome microarray (52 samples) and bioinformatics analysis. Subsequently, these candidate TAAbs were further confirmed by indirect ELISA with two testing cohorts (120 samples for verification and 663 samples for validation). The AUC for these four TAAbs to identify patients with HBV-HCC from chronic hepatitis B (CHB) patients ranged from 0.693 to 0.739. Finally, a diagnostic panel with three TAAbs (anti-ZIC2, anti-CDC37L1, and anti-DUSP6) was developed. This panel showed superior diagnostic efficiency in identifying early HBV-HCC compared with alpha-fetoprotein (AFP), with an AUC of 0.834 [95% confidence interval (CI), 0.772-0.897] for this panel and 0.727 (95% CI, 0.642-0.812) for AFP (P = 0.0359). In addition, the AUC for this panel to identify AFP-negative patients with HBV-HCC was 0.796 (95% CI, 0.734-0.858), with a sensitivity of 52.4% and a specificity of 89.0%. Importantly, the panel in combination with AFP significantly increased the positive rate for early HBV-HCC to 84.1% (P = 0.005) and for late HBV-HCC to 96.3% (P < 0.001). Our findings suggest that AFP and the autoantibody panel may be independent but complementary serologic biomarkers for HBV-HCC detection.

PREVENTION RELEVANCE

We developed a robust diagnostic panel for identifying patients with HBV-HCC from patients with CHB. This autoantibody panel provided superior diagnostic performance for HBV-HCC at an early stage and/or with negative AFP results. Our findings suggest that AFP and the autoantibody panel may be independent but complementary biomarkers for HBV-HCC detection.

A Luminex Approach to Develop an Anti-Tumor-Associated Antigen Autoantibody Panel for the Detection of Prostate Cancer in Racially/Ethnically Diverse Populations

(1) Background: Autoantibodies to tumor-associated antigens (TAAs) have emerged as promising cancer biomarkers. Luminex technology offers a powerful approach for the simultaneous detection of multiple anti-TAA autoantibodies. (2) Methods: We aimed to utilize Luminex technology to evaluate and optimize a panel of anti-TAAs autoantibodies for detecting prostate cancer (PCa), which included autoantibodies to fourteen TAAs. A total of 163 serum samples (91 PCa, 72 normal controls) were screened to determine the levels of the autoantibodies using the Luminex assay. (3) Results: Twelve autoantibodies exhibited significantly high frequencies ranging from 19.8% to 51.6% in the PCa group. Receiver operating characteristic (ROC) curve analysis revealed area under the curve (AUC) values ranging from 0.609 to 0.868 for the twelve autoantibodies individually. We further confirmed the performance of the HSP60 autoantibody by using an enzyme-linked immunosorbent assay (ELISA) in a larger sample comprising 200 PCa sera, 20 benign prostatic hyperplasia (BPH) sera, and 137 normal control sera. The results obtained from the Luminex assay were consistent with the ELISA findings. We developed a panel consisting of three autoantibodies (p16, IMP2, and HSP60) which achieved an impressive AUC of 0.910 with a sensitivity of 71.4% and a specificity of 95.8%. The panel was also evaluated in PCa patients from different races/ethnicities with the best performance observed in distinguishing the Hispanic American patients with PCa from normal controls. (4) Conclusions: We developed an anti-TAA autoantibody panel for the detection of PCa that exhibits promising performance. This panel holds significant potential as a high-throughput tool to facilitate PCa detection.

Liquid Biopsy for Lung Cancer: Up-to-Date and Perspectives for Screening Programs

Lung cancer is the deadliest cancer worldwide. Tissue biopsy is currently employed for the diagnosis and molecular stratification of lung cancer. Liquid biopsy is a minimally invasive approach to determine biomarkers from body fluids, such as blood, urine, sputum, and saliva. Tumor cells release cfDNA, ctDNA, exosomes, miRNAs, circRNAs, CTCs, and DNA methylated fragments, among others, which can be successfully used as biomarkers for diagnosis, prognosis, and prediction of treatment response. Predictive biomarkers are well-established for managing lung cancer, and liquid biopsy options have emerged in the last few years. Currently, detecting EGFR p.(Tyr790Met) mutation in plasma samples from lung cancer patients has been used for predicting response and monitoring tyrosine kinase inhibitors (TKi)-treated patients with lung cancer. In addition, many efforts continue to bring more sensitive technologies to improve the detection of clinically relevant biomarkers for lung cancer. Moreover, liquid biopsy can dramatically decrease the turnaround time for laboratory reports, accelerating the beginning of treatment and improving the overall survival of lung cancer patients. Herein, we summarized all available and emerging approaches of liquid biopsy-techniques, molecules, and sample type-for lung cancer.

The Importance of the Immune System and Molecular Cell Signaling Pathways in the Pathogenesis and Progression of Lung Cancer

Lung cancer is a disease that in recent years has become one of the greatest threats to modern society. Every year there are more and more new cases and the percentage of deaths caused by this type of cancer increases. Despite many studies, scientists are still looking for answers regarding the mechanisms of lung cancer development and progression, with particular emphasis on the role of the immune system. The aim of this literature review was to present the importance of disorders of the immune system and the accompanying changes at the level of cell signaling in the pathogenesis of lung cancer. The collected results showed that in the process of immunopathogenesis of almost all subtypes of lung cancer, changes in the tumor microenvironment, deregulation of immune checkpoints and abnormalities in cell signaling pathways are involved, which contribute to the multistage and multifaceted carcinogenesis of this type of cancer. We, therefore, suggest that in future studies, researchers should focus on a detailed analysis of tumor microenvironmental immune checkpoints, and to validate their validity, perform genetic polymorphism analyses in a wide range of patients and healthy individuals to determine the genetic susceptibility to lung cancer development. In addition, further research related to the analysis of the tumor microenvironment; immune system disorders, with a particular emphasis on immunological checkpoints and genetic differences may contribute to the development of new personalized therapies that improve the prognosis of patients.

Blood protein biomarkers in lung cancer

Lung cancer has consistently ranked first as the cause of cancer-associated mortality. The 5-year survival rate has risen slowly, and the main obstacle to improving the prognosis of patients has been that lung cancer is usually diagnosed at an advanced or incurable stage. Thus, early detection and timely intervention are the most effective ways to reduce lung cancer mortality. Tumor-specific molecules and cellular elements are abundant in circulation, providing real-time information in a noninvasive and cost-effective manner during lung cancer development. These circulating biomarkers are emerging as promising tools for early detection of lung cancer and can be used to supplement computed tomography screening, as well as for prognosis prediction and treatment response monitoring. Serum and plasma are the main sources of circulating biomarkers, and protein biomarkers have been most extensively studied. In this review, we summarize the research progress on three most common types of blood protein biomarkers (tumor-associated antigens, autoantibodies, and exosomal proteins) in lung cancer. This review will potentially guide researchers toward a more comprehensive understanding of candidate lung cancer protein biomarkers in the blood to facilitate their translation to the clinic.

Recent Advances in DNA Vaccines against Lung Cancer: A Mini Review

Lung cancer is regarded as the major causes of patient death around the world. Although the novel tumor immunotherapy has made great progress in the past decades, such as utilizing immune checkpoint inhibitors or oncolytic viruses, the overall 5-year survival of patients with lung cancers is still low. Thus, development of effective vaccines to treat lung cancer is urgently required. In this regard, DNA vaccines are now considered as a promising immunotherapy strategy to activate the host immune system against lung cancer. DNA vaccines are able to induce both effective humoral and cellular immune responses, and they possess several potential advantages such as greater stability, higher safety, and being easier to manufacture compared to conventional vaccination. In the present review, we provide a global overview of the mechanism of cancer DNA vaccines and summarize the innovative neoantigens, delivery platforms, and adjuvants in lung cancer that have been investigated or approved. Importantly, we highlight the recent advance of clinical studies in the field of lung cancer DNA vaccine, focusing on their safety and efficacy, which might accelerate the personalized design of DNA vaccine against lung 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.

Dual Effect of Immune Cells within Tumour Microenvironment: Pro- and Anti-Tumour Effects and Their Triggers

Our body is constantly exposed to pathogens or external threats, but with the immune response that our body can develop, we can fight off and defeat possible attacks or infections. Nevertheless, sometimes this threat comes from an internal factor. Situations such as the existence of a tumour also cause our immune system (IS) to be put on alert. Indeed, the link between immunology and cancer is evident these days, with IS being used as one of the important targets for treating cancer. Our IS is able to eliminate those abnormal or damaged cells found in our body, preventing the uncontrolled proliferation of tumour cells that can lead to cancer. However, in several cases, tumour cells can escape from the IS. It has been observed that immune cells, the extracellular matrix, blood vessels, fat cells and various molecules could support tumour growth and development. Thus, the developing tumour receives structural support, irrigation and energy, among other resources, making its survival and progression possible. All these components that accompany and help the tumour to survive and to grow are called the tumour microenvironment (TME). Given the importance of its presence in the tumour development process, this review will focus on one of the components of the TME: immune cells. Immune cells can support anti-tumour immune response protecting us against tumour cells; nevertheless, they can also behave as pro-tumoural cells, thus promoting tumour progression and survival. In this review, the anti-tumour and pro-tumour immunity of several immune cells will be discussed. In addition, the TME influence on this dual effect will be also analysed.

Detection and Quantification of Tp53 and p53-Anti-p53 Autoantibody Immune Complex: Promising Biomarkers in Early Stage Lung Cancer Diagnosis

Lung cancer is a leading cause of death worldwide, claiming nearly 1.80 million lives in 2020. Screening with low-dose computed tomography (LDCT) reduces lung cancer mortality by about 20% compared to standard chest X-rays among current or heavy smokers. However, several reports indicate that LDCT has a high false-positive rate. In this regard, methods based on biomarker detection offer excellent potential for developing noninvasive cancer diagnostic tests to complement LDCT for detecting stage 0∼IV lung cancers. Herein, we have developed a method for detecting and quantifying a p53-anti-p53 autoantibody complex and the total p53 antigen (wild and mutant). The LOD for detecting Tp53 and PIC were 7.41 pg/mL and 5.74 pg/mL, respectively. The detection ranges for both biomarkers were 0–7500 pg/mL. The known interfering agents in immunoassays such as biotin, bilirubin, intra-lipid, and hemoglobin did not detect Tp53 and PIC, even at levels that were several folds higher levels than their normal levels. Furthermore, the present study provides a unique report on this preliminary investigation using the PIC/Tp53 ratio to detect stage I–IV lung cancers. The presented method detects lung cancers with 81.6% sensitivity and 93.3% specificity. These results indicate that the presented method has high applicability for the identification of lung cancer patients from the healthy population.

A Diagnostic Model With IgM Autoantibodies and Carcinoembryonic Antigen for Early Detection of Lung Adenocarcinoma

Immunoglobulin M (IgM) autoantibodies, as the early appearing antibodies in humoral immunity when stimulated by antigens, might be excellent biomarkers for the early detection of lung cancer (LC). We aimed to develop a multi-analyte integrative model combining IgM autoantibodies and a traditional tumor biomarker that could be a valuable and powerful auxiliary diagnostic tool and might improve the accuracy of early detection of lung adenocarcinoma (LUAD). A customized protein array based on cancer driver genes was constructed and applied in the discovery cohort consisting of 68 LUAD patients and 68 normal controls (NCs); 31 differentially expressed IgM autoantibodies were identified. The top 5 candidate IgM autoantibodies [based on the area under the receiver operating characteristic curve (AUC) ranking], namely, TSHR, ERBB2, survivin, PIK3CA, and JAK2, were validated in the validation cohort using enzyme-linked immunosorbent assay (ELISA), which included 147 LUAD samples, 72 lung squamous cell carcinoma (LUSC) samples, 44 small cell lung carcinoma (SCLC) samples, and 147 NCs. These indicators presented diagnostic capacity for LUAD, with AUCs of 0.599, 0.613, 0.579, 0.601, and 0.633, respectively (p < 0.05). However, none of them showed a significant difference between the SCLC and NC groups, and only the IgM autoantibody against JAK2 showed a higher expression in LUSC than in NC (p = 0.046). Through logistic regression analysis, with the five IgM autoantibodies and carcinoembryonic antigen (CEA), one diagnostic model was constructed for LUAD. The model yielded an AUC of 0.827 (sensitivity = 56.63%, specificity = 93.98%). The diagnostic efficiency was superior to that of either CEA (AUC = 0.692) or IgM autoantibodies alone (AUC = 0.698). Notably, the accuracy of this model in early-stage LUAD reached 83.02%. In conclusion, we discovered and identified five novel IgM indicators and developed a multi-analyte model combining IgM autoantibodies and CEA, which could be a valuable and powerful auxiliary diagnostic tool and might improve the accuracy of early detection of LUAD.

A novel immunodiagnosis panel for hepatocellular carcinoma based on bioinformatics and the autoantibody-antigen system

Hepatocellular carcinoma (HCC) is a malignancy with a dismal survival rate. The novel autoantibodies panel may provide new insights for the diagnosis of HCC. Biomarkers screened by two methods (bioinformatics and the antigen‐antibody system) were taken as candidate tumor‐associated antigens (TAAs). Enzyme‐linked immunosorbent assay was used to detect the corresponding autoantibodies in 888 samples of verification and validation cohorts. The verification cohort was used to verify the autoantibodies. Samples in the validation cohort were randomly divided into a train set and a test set with the ratio of 6:4. A diagnostic model was established by support vector machines within the train set. The test set further verified the model. Eleven TAAs were selected (AAGAB, C17orf75, CDC37L1, DUSP6, EID3, PDIA2, RGS20, PCNA, TAF7L, TBC1D13, and ZIC2). The titer of six autoantibodies (PCNA, AAGAB, CDC37L1, TAF7L, DUSP6, and ZIC2) had a significant difference in any of the pairwise comparisons among the HCC, liver cirrhosis, and normal control groups. The titer of these autoantibodies had an increasing tendency. Finally, an optimum diagnostic model was constructed with the six autoantibodies. The AUCs were 0.826 in the train set and 0.773 in the test set. The area under the curve (AUC) of this panel for diagnosing early HCC was 0.889. The diagnostic ability of the panel reduced with the progress of HCC. The positive rate of the panel in diagnosing alpha‐fetoprotein (AFP)‐negative patients was 75.6%. For early HCC, the sensitivity of the combination of AFP with the panel was 90.9% and superior to 53.2% of AFP alone. The novel immunodiagnosis panel combining AFP may be a new approach for the diagnosis of HCC, especially for early‐HCC cases.

Detection of Circulating Antibodies to p16 Protein-Derived Peptides in Hepatocellular Carcinoma

OBJECTIVE

This study aimed at confirming the alteration of circulating anti-p16 immunoglobulin G (IgG) levels in hepatocellular carcinoma (HCC).

METHODS

An in-house-developed enzyme-linked immunosorbent assay was used for determining plasma IgG antibodies against p16-derived antigens in 122 HCC patients and 134 healthy controls.

RESULTS

Plasma anti-p16 IgG levels were significantly higher in HCC patients than in the controls (Z = 3.51, P = 0.0004), with no difference between males and females. A trend of increasing plasma anti-p16 IgG levels was associated with increasing HCC stage, with group 3 patients having the highest anti-p16 IgG levels (Z = 3.38, P = 0.0008). Group 3 exhibited the best sensitivity (19.6%) and specificity (95%) for plasma anti-p16 IgG detection, with an area under the receiver operating characteristic curve of 0.659 (95% confidence interval, 0.564-0.754).

CONCLUSION

Circulating IgG antibody to p16 protein might be a useful biomarker for HCC prognosis assessment rather than for early malignancy diagnosis.

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.

Identification of Novel Autoantibodies Based on the Human Proteomic Chips and Evaluation of Their Performance in the Detection of Gastric Cancer

Autoantibodies against tumor-associated antigens (TAAbs) can be used as potential biomarkers in the detection of cancer. Our study aims to identify novel TAAbs for gastric cancer (GC) based on human proteomic chips and construct a diagnostic model to distinguish GC from healthy controls (HCs) based on serum TAAbs. The human proteomic chips were used to screen the candidate TAAbs. Enzyme-linked immunosorbent assay (ELISA) was used to verify and validate the titer of the candidate TAAbs in the verification cohort (80 GC cases and 80 HCs) and validation cohort (192 GC cases, 128 benign gastric disease cases, and 192 HCs), respectively. Then, the diagnostic model was established by Logistic regression analysis based on OD values of candidate autoantibodies with diagnostic value. Eleven candidate TAAbs were identified, including autoantibodies against INPP5A, F8, NRAS, MFGE8, PTP4A1, RRAS2, RGS4, RHOG, SRARP, RAC1, and TMEM243 by proteomic chips. The titer of autoantibodies against INPP5A, F8, NRAS, MFGE8, PTP4A1, and RRAS2 were significantly higher in GC cases while the titer of autoantibodies against RGS4, RHOG, SRARP, RAC1, and TMEM243 showed no difference in the verification group. Next, six potential TAAbs were validated in the validation cohort. The titer of autoantibodies against F8, NRAS, MFGE8, RRAS2, and PTP4A1 was significantly higher in GC cases. Finally, an optimal prediction model with four TAAbs (anti-NRAS, anti-MFGE8, anti-PTP4A1, and anti-RRAS2) showed an optimal diagnostic performance of GC with AUC of 0.87 in the training group and 0.83 in the testing group. The proteomic chip approach is a feasible method to identify TAAbs for the detection of cancer. Moreover, the panel consisting of anti-NRAS, anti-MFGE8, anti-PTP4A1, and anti-RRAS2 may be useful to distinguish GC cases from HCs.

The neglected brothers come of age: B cells and cancer

The opposing roles of innate and adaptive immune cells in suppressing or supporting cancer initiation, progression, metastasis and response to therapy has been long debated. The mechanisms by which different monocyte and T cell subtypes affect and modulate cancer have been extensively studied. However, the role of B cells and their subtypes have remained elusive, perhaps partially due to their heterogeneity and range of actions. B cells can produce a variety of cytokines and present tumor-derived antigens to T cells in combination with co-stimulatory or inhibitory ligands based on their phenotype. Unlike most T cells, B cells can be activated by innate immune stimuli, such as endotoxin. Furthermore, the isotype and specificity of the antibodies produced by plasma cells regulate distinct immune responses, including opsonization, antibody-mediated cellular cytotoxicity (ADCC) and complement activation. B cells are shaped by the tumor environment (TME), with the capability to regulate the TME in return. In this review, we will describe the mechanisms of B cell action, including cytokine production, antigen presentation, ADCC, opsonization, complement activation and how they affect tumor development and response to immunotherapy. We will also discuss how B cell fate within the TME is affected by tumor stroma, microbiome and metabolism.

Humoral immune response to epidermal growth factor receptor in lung cancer

The aim of this study was to explore the potential value of autoantibody to epidermal growth factor receptor (EGFR) in the diagnosis of lung cancer (LC) and its relation with EGFR mutations. Enzyme-linked immunosorbent assay (ELISA) was performed to detect the level of autoantibody to EGFR in sera from 254 LC patients and 222 normal controls (NCs). Besides, the mRNA and protein levels of EGFR were investigated in Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) database, respectively. The level of autoantibody to EGFR (anti-EGFR) in LC even different types of LC was obviously higher than that in NC (P < 0.05). The area under the curve (AUC) of anti-EGFR was 0.695 (95% CI 0.645-0.742) when comparing LC patients with NC, while the AUC of carcinoembryonic antigen (CEA) was 0.681 (95% CI 0.629-0.730). Moreover, by integrating anti-EGFR with CEA to diagnose LC, the AUC was up to 0.784 (95% CI 0.737-0.826). However, the expression level of autoantibody to EGFR had no difference between LC patients with and without EGFR gene mutation (P > 0.05). EGFR mRNA expression level was obviously upregulated in squamous cell carcinoma (SCC) tissues compared with normal tissues (P < 0.05), but not in adenocarcinoma (ADC) (P > 0.05). The study confirmed that anti-EGFR could be a potential biomarker for LC diagnosis; additionally, it could improve the diagnostic value of CEA in clinical work.

Autoantibodies against p53, MMP-7, and Hsp70 as Potential Biomarkers for Detection of Nonmelanoma Skin Cancers

Basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are two predominant histological types of nonmelanoma skin cancer (NMSC), lacking effective early diagnostic markers. In this study, we assessed the diagnostic value of autoantibodies against p53, MMP-7, and Hsp70 in skin SCC and BCC. ELISA was performed to detect levels of autoantibodies in sera from 101 NMSC patients and 102 normal controls, who were recruited from the Cancer Hospital of Shantou University Medical College. A receiver operator characteristic curve was used to evaluate the diagnostic value. The serum levels of autoantibodies against p53, MMP-7, and Hsp70 were higher in NMSCs than those in the normal controls (all P < 0.01). The AUC of the three-autoantibody panel was 0.841 (95% CI: 0.788-0.894) with the sensitivity and specificity of 60.40% and 91.20% when differentiating NMSCs from normal controls. Furthermore, measurement of this panel could differentiate early-stage skin cancer patients from normal controls (AUC: 0.851; 95% CI: 0.793-0.908). Data from Oncomine showed that the level of p53 mRNA was elevated in BCC (P < 0.05), and the Hsp70 mRNA was upregulated in SCC (P < 0.001). This serum three-autoantibody panel might function in assisting the early diagnosis of NMSC.

Discovery and Validation of Serum Autoantibodies Against Tumor-Associated Antigens as Biomarkers in Gastric Adenocarcinoma Based on the Focused Protein Arrays

INTRODUCTION:

Previous studies have demonstrated that autoantibodies against tumor-associated antigens (TAAs) in patients with cancer can be used as sensitive immunodiagnostic biomarkers for the detection of cancer. Most of these TAAs are involved in the tumorigenesis pathway. Cancer driver genes with intragenic mutations can promote tumorigenesis. This study aims to identify autoantibodies against TAAs encoded by cancer driver genes in sera as potential immunodiagnostic biomarkers for gastric adenocarcinoma (GAC).

METHODS:

Protein arrays based on cancer driver genes were customized for screening candidate TAAs in 100 GAC sera and 50 normal control (NC) sera. Autoantibodies against candidate TAAs were assessed by enzyme-linked immunosorbent assay in both training group (205 GAC sera and 205 NC sera) and independent validation group (126 GAC sera and 126 NC sera). Moreover, the immunodiagnostic models were respectively established and validated in the training group and validation group.

RESULTS:

A panel with 5 autoantibodies including anti-TP53, anti-COPB1, anti-GNAS, anti–serine/arginine-rich splicing factor 2, and anti-SMARCB1 was selected by the Fisher linear discriminant analysis model with an areas under receiver operating characteristic curve (AUC) of 0.928 (95% confidence interval [CI]: 0.888–0.967) in the training cohort and an AUC of 0.885 (95% CI: 0.852–0.918) in the validation cohort. Besides, the panel with 5 autoantibodies including anti-TP53, anti-COPB1, anti-GNAS, anti-PBRM1, and anti-ACVR1B which were selected by the binary logistic regression model showed an AUC of 0.885 (95% CI: 0.852–0.919) in the training cohort and 0.884 (95% CI: 0.842–0.925) in the validation cohort.

DISCUSSION:

Two panels which were selected in this study could boost the detection of anti-TAA autoantibodies in sera as biomarkers for the detection of GAC.

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.

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.

Identification of novel autoantibodies based on the protein chip encoded by cancer-driving genes in detection of esophageal squamous cell carcinoma

The purpose of this study was to identify novel autoantibodies against tumor-associated antigens (TAAbs) and explore the optimal diagnosis model based on the protein chip for detecting esophageal squamous cell carcinoma (ESCC). The human protein chip based on cancer-driving genes was customized to discover candidate TAAbs. Enzyme-linked immunosorbent assay was applied to verify and validate the expression levels of candidate TAAbs in the training cohort (130 ESCC and 130 normal controls) and the validation cohort (125 ESCC and 125 normal controls). Logistic regression analysis was adopted to construct the diagnostic model based on the expression levels of autoantibodies with diagnostic value. Twelve candidate autoantibodies were identified based on the protein chip according to the corresponding statistical methods. In both the training cohort and validation cohort, the expression levels of 10 TAAbs (GNA11, PTEN, P53, SRSF2, GNAS, ACVR1B, CASP8, DAXX, PDGFRA, and MEN1) in ESCC patients were higher than that in normal controls. The panel consisting of GNA11, ACVR1B and P53 demonstrated favorable diagnostic power. The sensitivity, specificity and accuracy of the model in the train cohort and the validation cohort were 71.5%, 93.8%, 79.6% and 77.6%, 81.6%, 70.8%, respectively. In either cohort, there was no correlation between positive rate of the autoantibody panel and clinicopathologic features for ESCC patients. Protein chip technology is an effective method to identify novel TAAbs, and the panel of 3 TAAbs (GNA11, ACVR1B, and P53) is promising for distinguishing ESCC patients from normal individuals.

Competitive learning suggests circulating miRNA profiles for cancers decades prior to diagnosis

MicroRNAs are regulators of gene expressionand may be key markers in liquid biopsy.Early diagnosis is an effective means to increase patients' overall survival. We generated genome-wide miRNA profiles from serum of patients and controls from the population-based Janus Serum Bank (JSB) and analysed them by bioinformatics and artificial intelligence approaches. JSB contains sera from 318,628 originally healthy persons, more than 96,000 of whom developed cancer. We selected 210 serum samples from patients with lung, colon or breast cancer at three time points prior to diagnosis (up to 32 years prior to diagnosis with median 5 years interval between TPs), one time-point after diagnosis and from individually matched controls. The controls were matched on age and year of all pre-diagnostic sampling time-points for the corresponding case. Using ANOVA we report 70 significantly deregulated markers (adjusted p-value<0.05). The driver for the significance was the diagnostic time point (miR-575, miR-6821-5p, miR-630 with adjusted p-values<10^-10). Further, 91miRNAs were differently expressed in pre-diagnostic samples as compared to controls (nominal p < 0.05). Self-organized maps (SOMs)indicated larges effects in lung cancer samples while breast cancer samples showed the least pronounced changes. SOMsalsohighlighted cancer and time point specific miRNA dys-regulation. Intriguingly, a detailed breakdown of the results highlighted that 51% of all miRNAs were highly specific, either for a time-point or a cancer entity. Pathway analysis highlighted 12 pathways including Hipo signalling and ABC transporters.Our results indicate that tumours may be indicated by serum miRNAs decades prior the clinical manifestation.

Clinical value of seven autoantibodies combined detection in the diagnosis of lung cancer

Background

To analyze the clinical value of seven autoantibodies (p53, PGP9.5, SOX2, GAGE7, GBU4‐5, MAGE A1 and CAGE) in lung cancer patients.

Methods

ELISA was used to determine serum levels of seven autoantibodies in 177 patients with lung cancer, 201 healthy persons, and 210 patients with benign pulmonary diseases. Positive rates of 7 autoantibodies were analyzed; receiver operating characteristic (ROC) curves were drawn to analyze their diagnostic efficiency in lung cancer and to compare the positive rate of seven kinds of autoantibody combined detection of lung cancer patients with different clinicopathological features.

Results

The positive rate of seven autoantibodies in all subjects was 13.44%. The positive rate of seven autoantibodies in lung cancer was 25.42%. The positive rate of the combined detection of seven autoantibodies in the lung cancer group was significantly higher than that in healthy control group (χ² = 19.76, P < .001) and benign lung disease group (χ² = 21.44, P < .001). Sensitivity, specificity, and AUC^ROC of the seven autoantibodies were 25.42%, 91.75%, and 0.683, respectively. Sensitivity and AUC^ROC were higher than those of the single autoantibody detection. Positive rates of seven autoantibodies in different pathological types and clinical stages of lung cancer patients were significantly different (P < .05).

Conclusions

The combined detection of 7 autoantibodies in lung cancer has some clinical value for the auxiliary diagnosis of lung cancer.

Elevated plasma YKL-40 level is found in the dogs with cancer and is related to poor prognosis

YKL-40, a secreted glycoprotein, may serve as an autoantigen, which mediates multiple inflammatory diseases and cancers. A high YKL-40 serum level is correlated with metastasis and poor survival in a variety of human cancers. However, the role of YKL-40 in dogs is still under evaluation. Herein, we examined the associations between plasma YKL-40 level and YKL-40 autoantibody (YAA) titers with malignancy and prognosis in canine cancer. Plasma levels of YKL-40 in healthy dogs (n = 20) and in dogs (n = 82) with cancer were evaluated using enzyme-linked immunosorbent assay. Our results indicated that plasma YKL-40 levels were significantly higher (p < 0.01) in dogs with cancer than in healthy dogs. A significant decrease in the YAA titers was detected in the dogs with cancer when compared with those of the healthy dogs (p < 0.05), although the change was not correlated with the YKL-40 levels. Among the dogs with cancer, plasma YKL-40 levels in the dogs that later relapsed or had metastasis were significantly higher than in the dogs with no signs of relapse (p < 0.01) or metastasis (p <0.05). The relapse and metastasis rates were significantly higher in the high YKL-40 group (> 180 pg/mL) than in the low YKL-40 group (< 180 pg/mL). The results imply that plasma YKL-40 levels might have the potential to be developed as a marker of malignancy progression and prognosis in canine cancers.

Discovering novel lung cancer associated antigens and the utilization of their autoantibodies in detection of lung cancer

OBJECTIVE

The identification of tumor-associated antigens (TAAs) and their corresponding autoantibodies in lung cancer (LC) may expand our vision of cancer immunity. This study aims to screen novel TAAs to distinguish LC from the healthy population.

METHODS

In our previous study, 35 genes encoding LC-associated TAAs were identified from the serological analysis of recombinant cDNA expression libraries (SEREX), and Oncomine database was further used to identify potential genes in cancer progression. Autoantibody to TAAs were tested by enzyme-linked immunosorbent assay (ELISA) in sera from 1379 participants in validation set and verification set.

FINDINGS

Based on analysis of three independent microarrays in Oncomine, ten genes were consistently dysregulated in LC. The sera level and positive frequency of the anti-TOP2A, anti-ACTR3, anti-RPS6KA5 and anti-PSIP1 from LC patients were higher than normal control in validation set. The area under curve (AUC) of anti-TOP2A, anti-ACTR3, anti-RPS6KA5 and anti-PSIP1 was respectively 0.758, 0.787, 0.707, 0.668. The sensitivity of these four autoantibodies for LC detection ranged from 26.63 % to 32.07 % with the specificity over 90 %. Data from the verification set confirmed the results. Except that, the frequency of serum autoantibody against TOP2A (43.3 %) and ACTR3 (50.0 %) was significantly higher in early stage LC than late stage (23.6 % and 22.3 %, respectively).

CONCLUSION

TOP2A, ACTR3, RPS6KA5 and PSIP1 can elicit humoral immune response in LC and their autoantibodies have relationship with the tumorigenesis of LC. Anti-TOP2A and anti-ACTR3 have the potential to serve as a serological biomarkers in early stage LC.

Intratumoral immunoglobulin isotypes predict survival in lung adenocarcinoma subtypes

BACKGROUND

The role of tumor-infiltrating B-cells (TIBs) and intratumorally-produced antibodies in cancer-immunity interactions essentially remains terra incognita. In particular, it remains unexplored how driver mutations could be associated with distinct TIBs signatures and their role in tumor microenvironment.

METHODS

Here we analyzed associations of immunoglobulin isotypes and clonality with survival in TCGA RNA-Seq data for lung adenocarcinoma (LUAD), stratifying patients into 12 driver mutation and phenotypic tumor subgroups.

RESULTS

We revealed several unexpected associations between TIBs behavior and prognosis. Abundance and high proportion of IgG1 isotype, and low proportion of IgA among all intratumorally produced immunoglobulins were specifically associated with improved overall survival for KRAS^mut but not KRAS^wt LUAD, revealing the first link between a driver mutation and B-cell response. We found specific IgG1 signature associated with long survival, which suggests that particular specificities of IgG1+ TIBs could be beneficial in KRAS^mut LUAD. In contrast to our previous observations for melanoma, highly clonal IgG1 production by plasma cells had no meaningful effect on prognosis, suggesting that IgG1+ TIBs may exert a beneficial effect in KRAS^mut cases in an alternative way, such as efficient presentation of cognate antigens or direct B cell attack on tumor cells. Notably, a high proportion of the IgG1 isotype is positively correlated with the non-silent mutation burden both in the general LUAD cohort and in most patient subgroups, supporting a role for IgG1⁺ TIBs in antigen presentation. Complementing the recent finding that the presence of stromal IgG4-producing cells is associated with a favorable prognosis for patients with stage I squamous cell carcinoma, we show that the abundance of IgG4-producing TIBs likewise has a strong positive effect on overall survival in STK11^mut and proximal proliferative subgroups of LUAD patients. We hypothesize that the positive role of IgG4 antibodies in some of the lung cancer subtypes could be associated with reported inability of IgG4 isotype to form immune complexes, thus preventing immunosuppression via activation of the myeloid-derived suppressor cell (MDSC) phenotype.

CONCLUSIONS

We discover prominent and distinct associations between TIBs antibody isotypes and survival in lung adenocarcinoma carrying specific driver mutations. These findings indicate that particular types of tumor-immunity relations could be beneficial in particular driver mutation context, which should be taken into account in developing strategies of cancer immunotherapy and combination therapies. Specificity of protective B cell populations in specific cancer subgroups could become a clue to efficient targeted immunotherapies for appropriate cohorts of patients.

Screening of tumor-associated antigens based on Oncomine database and evaluation of diagnostic value of autoantibodies in lung cancer

OBJECTIVES

The purpose of this study is to discover novel tumor-associated antigens (TAAs) to improve the diagnosis of lung cancer (LC).

MATERIALS AND METHODS

Oncomine database was used to discover potential TAAs from LC tissues, enzyme-linked immunosorbent assay (ELISA) was used to detect the levels of autoantibodies against TAAs in two independent sets (identification set, n = 368; validation set, n = 1011).

RESULTS

Analyses of sera from identification set showed that the sensitivity of autoantibodies against five TAAs (HMGB3, ZWINT, GREM1, NUSAP1 and MMP12) reached 57.1%, 42.4%, 38.0%, 36.4% and 20.7%, with area under ROC curve (AUC) of 0.85, 0.75, 0.71, 0.73 and 0.70, respectively. It also validated the diagnostic performances of these autoantibodies with AUC of 0.72, 0.65, 0.61, 0.64 and 0.64, respectively. Autoantibody against HMGB3 exhibited significantly increased frequency in early LC (53.3%) compared to advanced LC (29.3%) (P < .05). The positive rates of autoantibody against HMGB3 and NUSAP1 in serum of LC patients without distant metastasis were significantly higher than that of distant metastatic LC (P < .05). When each of the three protein biomarkers (CEA, CA125 and CYFRA21-1) was combined with anti-HMGB3 autoantibody, the sensitivity of early LC increased to 72.7%, 63.3% and 75.9% from 36.4%, 13.3% and 27.6%, respectively.

CONCLUSION

Autoantibodies against 5 TAAs (HMGB3, ZWINT, GREM1, NUSAP1 and MMP12) might have favorable diagnostic values in LC detection, and autoantibody against HMGB3 has the potential to serve as a serological biomarker in early-stage LC. The combination of protein biomarkers and anti-HMGB3 might contribute to detection of early-stage LC.

Upregulated NPM1 is an independent biomarker to predict progression and prognosis of oral squamous cell carcinomas in Taiwan

BACKGROUND

Nucleophosmin/nucleoplasmin family 1 (NPM1) has broad physiological functions, such as DNA replication, transcription, ribosome biogenesis, and centrosome replication. This study explored the clinicopathological importance of NPM1 as a prognostic marker for oral squamous cell carcinoma (OSCC).

METHODS

We collected specimens from 96 OSCC, 45 oral epithelial dysplasia (OED), and 29 normal oral mucosa (NOM). NPM1 expression was analyzed via immunohistochemistry. Correlations between NPM1and clinical parameters were analyzed using Student t test, chi-squared test, and Kaplan-Meier product-limit method.

RESULTS

The NPM1 labeling indices (LIs) were significantly higher in OSCCs than in NOM and oral OED. Higher NPM1 expression was significantly correlated with larger tumor size, nodal metastasis, and advanced clinical stage. Multivariate analysis revealed that higher NPM1 LIs were an unfavorable independent factor for survival.

CONCLUSIONS

Upregulated NPM1 is an independent biomarker of poor prognosis and NPM1 inhibitors may be promising in molecular targeted therapy against OSCC.

Idiotypic and anti-idiotypic antibodies against polycyclic aromatic hydrocarbon in human blood serum are new biomarkers of lung cancer

Evaluation of epidemiologic risk factor in relation to lung cancer invoked by polycyclic aromatic hydrocarbons has been inconsistent. To address this issue, we conducted a prospective evaluation of new biomarkers for lung cancer classified according levels of idiotypic and anti-idiotypic antibodies against polycyclic aromatic hydrocarbons in human blood serum. The blood serums of 557 lung cancer patients and 227 healthy donors were analysis of these antibodies by ELISA. Collected data were regrouped and analyzed by gender, smoking, and age as predictors of risk lung cancer factors. Also, the data of lung cancer patients were additionally analyzed by stages and types of lung cancer, surgery, and chemotherapy. It was suggested to use ratio of idiotypic and anti-idiotypic antibodies rather than distinguish level each of them separately. The ratio of levels in healthy people was 3.32 times higher than in lung cancer patients. This approach gave more precisely results and great prognostic value. The logistic regression model (AUC = 0.9) and neural networks (AUC = 0.95) were built to compare lung cancer patients and healthy donors by predictors. The ELISA data of 49 people random sampled from the originally ELISA data and ELISA data of 52 coal miners as a group of lung cancer risk were confirmed logistic regression model. So, suggested idiotypic and anti-idiotypic antibodies against polycyclic aromatic hydrocarbons were not only shown difference between healthy donors and lung cancer patients also elicited group of lung cancer risk among healthy people.

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.

MGMT autoantibodies as a potential prediction of recurrence and treatment response biomarker for glioma patients

Background

Cancer‐specific autoantibodies found in serum of cancer patients have been characterized as potential predictors of the high risk of recurrence and treatment response. The objective of this study is to investigate the clinical utility of serum O‐6‐methylguanine‐DNA methyltransferase (MGMT) autoantibodies as novel biomarkers for prediction of recurrence and treatment response for glioma through MGMT peptides microarray.

Methods

A total of 201 serum samples of glioma patients with various WHO grade and 311 serum samples of healthy donors were examined for the detection of MGMT autoantibodies by peptides microarray. The clinical value of MGMT autoantibodies was studied through univariable and multivariable analyses.

Results

Autoantibodies to MGMT peptides were detected in sera from glioma patients and five highly responsive autoantibodies to peptides were identified in the glioma group. The positive rate of MGMT autoantibody to 20 peptides in glioma groups is compared with healthy individuals, the positive rate of MGMT‐02 (45%), MGMT‐04 (27%), MGMT‐07 (21%), MGMT‐10 (13%), and MGMT‐18 (24%) were significantly elevated in patients with glioma. MGMT autoantibody and its protein expression exhibited a significant correlation. The levels of MGMT autoantibodies decreased on the 30th day after operation, reaching preoperative levels, similar to those when tumor recurrence developed. Univariable and multivariable analyses revealed that the only preoperative autoantibodies to MGMT‐02 peptide were independently correlated with recurrence‐free survival. Preoperative seropositive patients were more likely than seronegative patients to have shorter recurrence times and to be resistant to chemoradiotherapy or chemotherapy with temozolomide.

Conclusion

Monitoring the levels of preoperative serum autoantibodies to MGMT‐02 peptide was useful for predicting patients at high risk of recurrence and treatment response.

The Relevance of Mass Spectrometry Analysis for Personalized Medicine through Its Successful Application in Cancer "Omics"

Mass spectrometry (MS) is an essential analytical technology on which the emerging omics domains; such as genomics; transcriptomics; proteomics and metabolomics; are based. This quantifiable technique allows for the identification of thousands of proteins from cell culture; bodily fluids or tissue using either global or targeted strategies; or detection of biologically active metabolites in ultra amounts. The routine performance of MS technology in the oncological field provides a better understanding of human diseases in terms of pathophysiology; prevention; diagnosis and treatment; as well as development of new biomarkers; drugs targets and therapies. In this review; we argue that the recent; successful advances in MS technologies towards cancer omics studies provides a strong rationale for its implementation in biomedicine as a whole.

Blood serum proteins as biomarkers for prediction of survival, locoregional control and distant metastasis rate in radiotherapy and radio-chemotherapy for non-small cell lung cancer

BACKGROUND

Several studies have documented that blood biomarkers can improve basic prognostic models in radiotherapy and radio-chemotherapy for non-small cell lung cancer. The current study evaluated the prognostic impact of six markers focusing on their utility in homogenous subsets, compared to the significance in a large heterogeneous group.

METHODS

Blood samples of 337 patients who were referred for curative or palliative external beam thoracic radiotherapy for non-small cell lung cancer were collected. The concentration of osteopontin (OPN), vascular endothelial growth factor (VEGF), erythropoetin (EPO), high mobility group box 1 protein (HMGB1), insulin-like growth factor 1 (IGF-1) and platelet-derived growth factor (PDGF) in serum were measured by ELISA assay and the prognostic potential was assessed using univariable and multivariable survival models.

RESULTS

Multivariable analysis revealed that out of several variables studied six dichotomized features: namely: cigarette smoking, lack of chemotherapy, palliative doses of radiotherapy, high OPN concentration, advanced T stage and high VEGF concentration had a highly significant (p < 0.005) and independent influence on overall survival in the group of 337 patients. In a subset of patients treated with curative radio-chemotherapy or radiotherapy (N = 148) tumor pathology, EPO concentration and VEGF concentration, significantly and independently influenced overall survival. In a subset of patients with squamous cell cancer (N = 206) OPN had a highly significant impact on overall survival. In contrast, in a subset of patients with nonsquamous histology (N = 131) only VEGF had a significant influence on survival.

CONCLUSIONS

Blood serum proteins appear to be clinically useful prognosticators of overall survival in radio-chemotherapy and radiotherapy for non-small cell lung cancer. In unselected heterogeneous groups, dichotomized concentrations of OPN and VEGF emerged among the strongest independent prognosticators of overall survival. VEGF and EPO concentration (dichotomized) were found to be independent prognostic factors among the patients treated with curative doses of radiotherapy. The utility of OPN as a prognostic marker appeared restricted to the patients with squamous histology.

Autoantibody against 14-3-3 zeta: a serological marker in detection of gastric cancer

PURPOSE

Autoantibody to 14-3-3 zeta was identified in gastric cancer (GC) by serological proteome analysis (SERPA) in our previous study. We comprehensively evaluated its ability to detect GC, determined its association with clinical characteristics, and explored its temporal change in GC patients before and after gastrectomy resection in this study.

METHODS

Anti-14-3-3 zeta antibody was examined by immunoassay in sera from 465 GC patients and 465 normal individuals, and also in 69 serial sera from 26 GC patients before and after resection.

RESULTS

The frequency of anti-14-3-3 zeta were significantly higher in GC group than in control group, with AUC of 0.627. The appearance of anti-14-3-3 zeta showed no difference in different tumor stage, tumor size, tumor differentiation, and lymphatic metastasis, but was higher in GC patients with family tumor history than without family tumor history. When anti-14-3-3 zeta was combined with clinical markers (CEA, CA199 and CA724), the sensitivity increased to 52.7%. In the follow-up analysis, the titer of anti-14-3-3 zeta was higher in post-resection sera than pre-resection sera, and no difference was observed in CEA, CA199 and CA724. Anti-14-3-3 zeta showed an increase from negative status to positive status in six patients after resection, while other three clinical markers presented different change in GC patients after resection.

CONCLUSIONS

Autoantibody against 14-3-3 zeta could be a potential diagnostic biomarker and improve the sensitivity of CEA, CA199 and CA724 in diagnosis of GC. Further largescale studies will be needed to validate its performance in GC patients after resection.

Preferential Localization of MUC1 Glycoprotein in Exosomes Secreted by Non-Small Cell Lung Carcinoma Cells

Lung cancer remains to be the leading cause of cancer-related mortality worldwide. Finding new noninvasive biomarkers for lung cancer is still a significant clinical challenge. Exosomes are membrane-bound, nano-sized vesicles that are released by various living cells. Studies on exosomal proteomics may provide clues for developing clinical assays. In this study, we performed semi-quantitative proteomic analysis of proteins that were purified from exosomes of NCI-H838 non-small cell lung cancer cell line, with total cellular membrane proteins as control. In the exosomes, LC-MS/MS by data-independent analysis mode identified 3235 proteins. THBS1, ANXA6, HIST1H4A, COL18A1, MDK, SRGN, ENO1, TUBA4A, SLC3A2, GPI, MIF, MUC1, TALDO1, SLC7A5, ICAM1, HSP90AA1, G6PD, and LRP1 were found to be expressed in exosomes at more than 5-fold higher level as compared to total cellular membrane proteins. A well-known cancer biomarker, MUC1, is expressed at 8.98-fold higher in exosomes than total cellular membrane proteins. Subsequent analysis of plasma exosomes from non-small cell lung cancer (NSCLC) patients by a commercial electrochemiluminescence immunoassay showed that exosomal MUC1 level is 1.5-fold higher than healthy individuals (mean value 1.55 ± 0.16 versus mean value 1.05 ± 0.06, p = 0.0213). In contrast, no significant difference of MUC1 level was found between NSCLC patients and healthy individuals' plasma (mean value 5.48 ± 0.65 versus mean value 4.16 ± 0.49). These results suggest that certain proteins, such as MUC1, are selectively enriched in the exosome compartment. The mechanisms for their preferential localization and their biological roles remain to be studied.

Detection of autoantibodies against cancer-testis antigens in non-small cell lung cancer

OBJECTIVES

Cancer-testis antigens (CTAs) are defined as proteins that are specifically expressed in testis or placenta and their expression is frequently activated in cancer. Due to their ability to induce an immune response, CTAs may serve as suitable targets for immunotherapy. The aim of this study was to evaluate if there is reactivity against CTAs in the plasma of non-small cell lung cancer (NSCLC) patients through the detection of circulating antibodies.

MATERIALS AND METHODS

To comprehensively analyze autoantibodies against CTAs the multiplexing capacities of suspension bead array technology was used. Bead arrays were created with 120 protein fragments, representing 112 CTAs. Reactivity profiles were measured in plasma samples from 133 NSCLC patients and 57 cases with benign lung diseases.

RESULTS

Altogether reactivity against 69 antigens, representing 81 CTAs, was demonstrated in at least one of the analyzed samples. Twenty-nine of the antigens (45 CTAs) demonstrated exclusive reactivity in NSCLC samples. Reactivity against cancer-testis antigen family 47; member A (CT47A) genes, P antigen family member 3 (PAGE3), variable charge X-linked (VCX), melanoma antigen family B1 (MAGEB1), lin-28 homolog B (LIN28B) and chromosome 12 open reading frame 54 (C12orf54) were only found in NSCLC patients at a frequency of 1%-4%. The presence of autoantibodies towards these six antigens was confirmed in an independent group of 34 NSCLC patients.

CONCLUSION

We identified autoantibodies against CTAs in the plasma of lung cancer patients. The reactivity pattern of autoantibodies was higher in cancer patients compared to the benign group, stable over time, but low in frequency of occurrence. The findings suggest that some CTAs are immunogenic and that these properties can be utilized as immune targets.

Epitope mapping of anti-ALK antibodies in children with anaplastic large cell lymphoma

Patients with Nucleophosmin (NPM)-Anaplastic lymphoma kinase (ALK)-positive anaplastic large cell lymphoma (ALCL) mount ALK autoantibodies. The titer of these autoantibodies inversely correlates with the risk of relapse. The epitopes recognized by these autoantibodies in NPM-ALK might be associated with different ALK-antibody levels. We used overlapping peptide microarray technology to analyze epitope-binding to NPM-ALK by plasma or serum from 129 ALK-positive ALCL patients and 21 controls. Antibodies present in sera from ALCL patients bound to epitopes mainly in the C-terminal region of the ALK portion of NPM-ALK (amino acid positions 469-496, 561-588, 617-644). Patients with higher ALK antibody titers detected the epitope 561-588 more frequently as well as three further epitopes at the N-terminus of the kinase domain compared to patients with intermediate and low titers. These results identify new potential target epitopes for immunotherapy in ALK-positive ALCL. The methodology can be adapted for more reproducible analyses of tumor antigen detection.

Blood based biomarkers beyond genomics for lung cancer screening

While there is considerable interest at the present time in the development of so-called liquid biopsy approaches for cancer detection based notably on circulating tumor DNA, there are other types of potential biomarkers that show promise for lung cancer screening and early detection. Here we review approaches and some of the promising markers based on proteomics, metabolomics and the immune response to tumor antigens in the form of autoantibodies.

Using a panel of multiple tumor-associated antigens to enhance autoantibody detection for immunodiagnosis of gastric cancer

Autoantibodies against tumor-associated antigens (TAAs) are attractive non-invasive biomarkers for detection of cancer due to their inherently stable in serum. Serum autoantibodies against 9 TAAs from gastric cancer (GC) patients and healthy controls were measured by enzyme-linked immunosorbent assay (ELISA). A logistic regression model predicting the risk of being diagnosed with GC in the training cohort (n = 558) was generated and then validated in an independent cohort (n = 372). Area under the receiver operating characteristic curve (AUC) was used to assess the diagnostic performance. Finally, an optimal prediction model with 6 TAAs (p62, c-Myc, NPM1, 14-3-3ξ, MDM2 and p16) showed a great diagnostic performance of GC with AUC of 0.841 in the training cohort and 0.856 in the validation cohort. The proportion of subjects being correctly defined were 78.49% in the training cohort and 81.99% in the validation cohort. This prediction model could also differentiate early-stage (stage I-II) GC patients from healthy controls with sensitivity/specificity of 76.60%/72.34% and 80.56%/79.17% in the training and validation cohort, respectively, and the overall sensitivity/specificity for early-stage GC were 78.92%/74.70% when being combined with two cohorts. This prediction model presented no significant difference for the diagnostic accuracy between early-stage and late-stage (stage III - IV) GC patients. The model with 6 TAAs showed a high diagnostic performance for GC detection, particularly for early-stage GC. This study further supported the hypothesis that a customized array of multiple TAAs was able to enhance autoantibody detection in the immunodiagnosis of GC.

Serological proteome analysis approach-based identification of ENO1 as a tumor-associated antigen and its autoantibody could enhance the sensitivity of CEA and CYFRA 21-1 in the detection of non-small cell lung cancer

Purpose

Lung cancer (LC) is the leading cause of cancer-related deaths for both male and female worldwide. Early detection of LC could improve five-year survival rate up to 48.8% compared to 3.3% of late/distant stage. Autoantibodies to tumor-associated antigens (TAAs) have been described as being present before clinical symptoms in lung and other cancers. We aimed to identify more TAAs to improve the performance for discovering non-small cell lung cancer (NSCLC) patients from healthy individuals.

Methods

Two independent sets were included in this study. Serological proteome analysis (SERPA) was used to identify TAAs from NSCLC cell line H1299 in a discovery set. In validation study, anti-ENO1 autoantibody was examined by immunoassay in sera from 242 patients with NSCLC and 270 normal individuals.

Results

A 47 KDa protein was identified to be alpha-enolase (ENO1) by using SERPA. Analysis of sera from 512 participants by ELISA showed significantly higher frequency of anti-ENO1 autoantibodies in NSCLC sera compared with the sera from normal individuals, with AUC (95%CI) of 0.589 (0.539-0.638, P=0.001). There was no significant difference in frequency of anti-ENO1 in different stages, histological or metastasis status of NSCLC. When anti-ENO1 detection was combined with other two tumor protein biomarkers (CEA and CYFRA 21-1), the sensitivity of NSCLC increased to 84%.

Conclusions

ENO1 can elicit humoral immune response in NSCLC and its autoantibody has association with the tumorigenesis of NSCLC. Furthermore, these intriguing results suggest the possibility of autoantibody against ENO1 serving as a potential diagnostic biomarker in NSCLC and have implications for defining novel histological determinants of NSCLC.

Early detection of hepatocellular carcinoma using autoantibody profiles from a panel of tumor-associated antigens

BACKGROUND

Multiple antigen miniarrays used for detecting autoantibodies to tumor-associated antigens (TAAs) can be a useful approach for cancer detection and diagnosis. We here address a very specific question: might there be autoimmune responses to TAAs which precede clinical detection of hepatocellular carcinoma (HCC) in HBV and HCV chronic liver disease patients under continuous medical surveillance, and if so, could these anti-TAAs be added to the armamentarium of diagnostic tests?

METHODS

We here examine the utility of a panel of 12 TAAs for the diagnosis of hepatocellular carcinoma (HCC). We derived a predictive rule for the presence of HCC based on the panel, from a cohort comprising 160 HCC patients and 90 normals. We then applied this rule to sequential anti-TAA data from a cohort of 17 HCC patients, from whom this information was available prior to diagnosis.

RESULTS

The predictors (autoantibodies to HCC1, P16, P53, P90, and survivin) indicated the presence of HCC prior to diagnosis in 16 of the 17 patients, at a median lead time of 0.75 year.

CONCLUSIONS

We believe these findings warrant further study of anti-TAA profiles as biomarkers for primary or early diagnosis of HCC.

Blood-based biomarkers in lung cancer: prognosis and treatment decisions

Despite recent advances, non-small cell lung cancer (NSCLC) remains a devastating disease with overall poor prognosis. Major contributing factors include obstacles to diagnosing the disease early in its course during the asymptomatic stage as well as diversity and complexity of its biology underlying tumorigenesis and tumor progression. Advances in molecularly targeted therapies which drives the development of personalized cancer care require precise and comprehensive understanding of tumor biology, not only at the time of diagnosis but also during treatment course and surveillance. As lung tumor tissue can be difficult to obtain without invasive and potentially risky procedures, it is difficult to monitor treatment response with serial tissue biopsies. Development of non-invasive but reliable blood based tumor markers has become an important research area. In this review, we focus on the following circulating biomarkers that have been identified in recent years: circulating tumor cells (CTCs); circulating cell-free nucleic acids, such as circulating tumor DNA (ctDNA) and microRNA (miR); and other biomarkers such as genomic and proteomic features. These biomarkers not only have prognostic values, but also can help guild treatment decisions by monitoring tumor burden, detecting minimal residual disease and/or recurrent disease, as well as monitoring evolution of genetic alterations throughout the treatment course.

The roles and applications of autoantibodies in progression, diagnosis, treatment and prognosis of human malignant tumours

The existence of autoantibodies towards an individual's own proteins or nucleic acids has been established for more than 100years, and for a long period, these autoantibodies have been believed to be closely associated with autoimmune diseases. However, in recent years, researchers have become more interested in the role and application of autoantibodies in progression, diagnosis, treatment and prognosis of human malignant tumours. Over the past few decades, numerous epidemiological studies have shown that the risk of certain cancers is significantly altered (increased or decreased) in patients with autoimmune diseases, which suggests that autoantibodies may play either promoting or suppressing roles in cancer progression. The idea that autoantibodies are directly involved in tumour progression gains special support by the findings that some antibodies secreted by a variety of cancer cells can promote their proliferation and metastasis. Because the cancer cells generate cell antigenic changes (neoantigens), which trigger the immune system to produce autoantibodies, serum autoantibodies against tumour-associated antigens have been established as a novel type of cancer biomarkers and have been extensively studied in different types of cancer. The autoantibodies as biomarkers in cancer diagnosis are not only more sensitive and specific than antigens, but also could appear before clinical evidences of the tumours, thus disclosing them. The observations that cancer risk is lower in patients with some autoimmune diseases suggest that certain autoantibodies may be protective from certain cancers. Moreover, the presence of autoantibodies in healthy individuals implies that it could be safe to employ autoantibodies to treat cancer. Of note, an autoantibodies derived from lupus murine model received much attention due to their selective cytotoxicity for malignant tumour cell without harming normal ones. These studies showed the therapeutic value of autoantibodies in cancer. In this review, we revisited the pathological or protective role of autoantibodies in cancer progression, summarize the application of autoantibodies in cancer diagnosis and prognosis, and discuss the value of autoantibodies in cancer therapy. The studies established to date suggest that autoantibodies not only regulate cancer progression but also promise to be valuable instruments in oncological diagnosis and therapy.

Identification of Serological Biomarkers for Early Diagnosis of Lung Cancer Using a Protein Array-Based Approach

Lung cancer (LC) remains the leading cause of mortality from malignant tumors worldwide. Currently, a lack of serological biomarkers for early LC diagnosis is a major roadblock for early intervention and prevention of LC. To undertake this challenge, we employed a two-phase strategy to discover and validate a biomarker panel using a protein array-based approach. In Phase I, we obtained serological autoimmune profiles of 80 LC patients and 20 healthy subjects on HuProt arrays, and identified 170 candidate proteins significantly associated with LC. In Phase II, we constructed a LC focused array with the 170 proteins, and profiled a large cohort, comprised of 352 LC patients, 93 healthy individuals, and 101 patients with lung benign lesions (LBL). The comparison of autoimmune profiles between the early stage LC and the combined group of healthy and LBL allowed us to identify and validate a biomarker panel of p53, HRas, and ETHE1 for diagnosis of early stage LC with 50% sensitivity at >90% specificity. Finally, the performance of this biomarker panel was confirmed in ELISA tests. In summary, this study represents one of the most comprehensive proteome-wide surveys with one of the largest (i.e. 1,101 unique samples) and most diverse (i.e. nine disease groups) cohorts, resulting in a biomarker panel with good performance.

Identification of 14‑3‑3ζ as a potential biomarker in gastric cancer by proteomics‑based analysis

The identification of tumor biomarkers to support early diagnosis and tumor progression monitoring may potentially reduce the mortality of gastric cancer (GC). The present study aimed to detect novel tumor‑associated antigens from the AGS GC cell line, and to identify their associated autoantibodies in sera from patients with GC by proteomics‑based approaches. Proteins from AGS cell lysates were isolated using two‑dimensional polyacrylamide gel electrophoresis, and western blotting was subsequently performed, to determine autoantibody responses in sera derived from patients with GC and healthy individuals. Positive protein spots were removed from gels stained with Coomassie blue, and were then evaluated by liquid chromatography‑tandem mass spectrometry. Sera from patients with GC produced numerous spots, one of which was identified as 14‑3‑3ζ. Autoantibody frequency to 14‑3‑3ζ was 17.6% (15/85) in patients with GC, which was significantly higher than that in healthy control individuals (2.4%; 2/85; P<0.01). These results suggested that the autoantibody against 14‑3‑3ζ may be a potential serological biomarker for the detection and diagnosis of GC.