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

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.

Update on Biomarkers for the Stratification of Indeterminate Pulmonary Nodules

Lung cancer is the leading cause of cancer-related deaths. Early detection and diagnosis are critical, as survival decreases with advanced stages. Approximately 1.6 million nodules are incidentally detected every year on chest CT scan images in the United States. This number of nodules identified is likely much larger after accounting for screening-detected nodules. Most of these nodules, whether incidentally or screening detected, are benign. Despite this, many patients undergo unnecessary invasive procedures to rule out cancer because our current stratification approaches are suboptimal, particularly for intermediate probability nodules. Thus, noninvasive strategies are urgently needed. Biomarkers have been developed to assist through the continuum of lung cancer care and include blood protein-based biomarkers, liquid biopsies, quantitative imaging analysis (radiomics), exhaled volatile organic compounds, and bronchial or nasal epithelium genomic classifiers, among others. Although many biomarkers have been developed, few have been integrated into clinical practice as they lack clinical utility studies showing improved patient-centered outcomes. Rapid technologic advances and large network collaborative efforts will continue to drive the discovery and validation of many novel biomarkers. Ultimately, however, randomized clinical utility studies showing improved patient outcomes will be required to bring biomarkers into clinical practice.

Development of a Novel Circulating Autoantibody Biomarker Panel for the Identification of Patients with 'Actionable' Pulmonary Nodules

Due to poor compliance and uptake of LDCT screening among high-risk populations, lung cancer is often diagnosed in advanced stages where treatment is rarely curative. Based upon the American College of Radiology's Lung Imaging and Reporting Data System (Lung-RADS) 80-90% of patients screened will have clinically "non-actionable" nodules (Lung-RADS 1 or 2), and those harboring larger, clinically "actionable" nodules (Lung-RADS 3 or 4) have a significantly greater risk of lung cancer. The development of a companion diagnostic method capable of identifying patients likely to have a clinically actionable nodule identified during LDCT is anticipated to improve accessibility and uptake of the paradigm and improve early detection rates. Using protein microarrays, we identified 501 circulating targets with differential immunoreactivities against cohorts characterized as possessing either actionable (n = 42) or non-actionable (n = 20) solid pulmonary nodules, per Lung-RADS guidelines. Quantitative assays were assembled on the Luminex platform for the 26 most promising targets. These assays were used to measure serum autoantibody levels in 841 patients, consisting of benign (BN; n = 101), early-stage non-small cell lung cancer (NSCLC; n = 245), other early-stage malignancies within the lung (n = 29), and individuals meeting United States Preventative Screening Task Force (USPSTF) screening inclusion criteria with both actionable (n = 87) and non-actionable radiologic findings (n = 379). These 841 patients were randomly split into three cohorts: Training, Validation 1, and Validation 2. Of the 26 candidate biomarkers tested, 17 differentiated patients with actionable nodules from those with non-actionable nodules. A random forest model consisting of six autoantibody (Annexin 2, DCD, MID1IP1, PNMA1, TAF10, ZNF696) biomarkers was developed to optimize our classification performance; it possessed a positive predictive value (PPV) of 61.4%/61.0% and negative predictive value (NPV) of 95.7%/83.9% against Validation cohorts 1 and 2, respectively. This panel may improve patient selection methods for lung cancer screening, serving to greatly reduce the futile screening rate while also improving accessibility to the paradigm for underserved populations.

Patients with ACPA-positive and ACPA-negative rheumatoid arthritis show different serological autoantibody repertoires and autoantibody associations with disease activity

Patients with rheumatoid arthritis (RA) can test either positive or negative for circulating anti-citrullinated protein antibodies (ACPA) and are thereby categorized as ACPA-positive (ACPA+) or ACPA-negative (ACPA-), respectively. In this study, we aimed to elucidate a broader range of serological autoantibodies that could further explain immunological differences between patients with ACPA+ RA and ACPA- RA. On serum collected from adult patients with ACPA+ RA (n = 32), ACPA- RA (n = 30), and matched healthy controls (n = 30), we used a highly multiplex autoantibody profiling assay to screen for over 1600 IgG autoantibodies that target full-length, correctly folded, native human proteins. We identified differences in serum autoantibodies between patients with ACPA+ RA and ACPA- RA compared with healthy controls. Specifically, we found 22 and 19 autoantibodies with significantly higher abundances in ACPA+ RA patients and ACPA- RA patients, respectively. Among these two sets of autoantibodies, only one autoantibody (anti-GTF2A2) was common in both comparisons; this provides further evidence of immunological differences between these two RA subgroups despite sharing similar symptoms. On the other hand, we identified 30 and 25 autoantibodies with lower abundances in ACPA+ RA and ACPA- RA, respectively, of which 8 autoantibodies were common in both comparisons; we report for the first time that the depletion of certain autoantibodies may be linked to this autoimmune disease. Functional enrichment analysis of the protein antigens targeted by these autoantibodies showed an over-representation of a range of essential biological processes, including programmed cell death, metabolism, and signal transduction. Lastly, we found that autoantibodies correlate with Clinical Disease Activity Index, but associate differently depending on patients' ACPA status. In all, we present candidate autoantibody biomarker signatures associated with ACPA status and disease activity in RA, providing a promising avenue for patient stratification and diagnostics.

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.

Bulk IgG glycosylation predicts COVID-19 severity and vaccine antibody response

Although vaccination efforts have expanded, there are still gaps in our understanding surrounding the immune response to SARS-CoV-2. Measuring IgG Fc glycosylation provides insight into an infected individual's inflammatory state, among other functions. We set out to interrogate bulk IgG glycosylation changes from SARS-CoV-2 infection and vaccination, using plasma from mild or hospitalized COVID-19 patients, and from vaccinated individuals. Inflammatory glycans are elevated in hospitalized COVID-19 patients and increase over time, while mild patients have anti-inflammatory glycans that increase over time, including increased sialic acid correlating with RBD antibody levels. Vaccinated individuals with low RBD antibody levels and low neutralization have the same IgG glycan traits as hospitalized COVID-19 patients. In addition, a small vaccinated cohort reveals a decrease in inflammatory glycans associated with peak IgG concentrations and neutralization. This report characterizes the bulk IgG glycome associated with COVID-19 severity and vaccine responsiveness and can help guide future studies into SARS-CoV-2 protective immunity.

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.

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.

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.

Clinical Application of Mass Spectrometry-Based Proteomics in Lung Cancer Early Diagnosis

The current knowledge on proteomic biomarker analysis for the early diagnosis of lung cancer is summarized, underlining the diversity among the results and the current interest in translating research results into clinical practice. A MEDLINE/PubMed literature search to retrieve all the papers published in the last 10 years is performed. Proteomics studies on lung cancer have gathered evidence on the potential role of biomarkers in early diagnosis. Although promising, none of them have proved to be sufficiently reliable to achieve validation. Future research should evolve toward a multipanel analysis of proteins, considering the possibility that individual biomarkers might not be specific enough to diagnose lung cancer, but could be related to oncological conditions.

Noninvasive biomarkers for lung cancer diagnosis, where do we stand?

The 2010's saw demonstration of the power of lung cancer screening to reduce mortality. However, with implementation of lung cancer screening comes the challenge of diagnosing millions of lung nodules every year. When compared to other cancers with widespread screening strategies (breast, colorectal, cervical, prostate, and skin), obtaining a lung nodule tissue biopsy to confirm a positive screening test remains associated with higher morbidity and cost. Therefore, non-invasive diagnostic biomarkers may have a unique opportunity in lung cancer to greatly improve the management of patients at risk. This review covers recent advances in the field of liquid biomarkers and computed tomographic imaging features, with special attention to new methods for combination of biomarkers as well as the use of artificial intelligence for the discrimination of benign from malignant nodules.

Fourier Transform Infrared Spectroscopy as a Cancer Screening and Diagnostic Tool: A Review and Prospects

Infrared spectroscopy has long been used to characterize chemical compounds, but the applicability of this technique to the analysis of biological materials containing highly complex chemical components is arguable. However, recent advances in the development of infrared spectroscopy have significantly enhanced the capacity of this technique in analyzing various types of biological specimens. Consequently, there is an increased number of studies investigating the application of infrared spectroscopy in screening and diagnosis of various diseases. The lack of highly sensitive and specific methods for early detection of cancer has warranted the search for novel approaches. Being more simple, rapid, accurate, inexpensive, non-destructive and suitable for automation compared to existing screening, diagnosis, management and monitoring methods, Fourier transform infrared spectroscopy can potentially improve clinical decision-making and patient outcomes by detecting biochemical changes in cancer patients at the molecular level. Besides the commonly analyzed blood and tissue samples, extracellular vesicle-based method has been gaining popularity as a non-invasive approach. Therefore, infrared spectroscopic analysis of extracellular vesicles could be a useful technique in the future for biomedical applications. In this review, we discuss the potential clinical applications of Fourier transform infrared spectroscopic analysis using various types of biological materials for cancer. Additionally, the rationale and advantages of using extracellular vesicles in the spectroscopic analysis for cancer diagnostics are discussed. Furthermore, we highlight the challenges and future directions of clinical translation of the technique for 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.

Multi-dimensional immunoproteomics coupled with in vitro recapitulation of oncogenic NRASQ61R identifies diagnostically relevant autoantibody biomarkers in thyroid neoplasia

Tumor-associated antigen (TAA)-specific autoantibodies have been widely implicated in cancer diagnosis. However, cancer cell lines that are typically exploited as candidate TAA sources in immunoproteomic studies may fail to accurately represent the autoantigen-ome of lower-grade neoplasms. Here, we established an integrated strategy for the identification of disease-relevant TAAs in thyroid neoplasia, which combined NRAS^Q61R oncogene expression in non-tumorous thyroid Nthy-ori 3-1 cells with a multi-dimensional proteomic technique DISER that consisted of profiling NRAS^Q61R-induced proteins using 2-dimensional difference gel electrophoresis (2D-DIGE) coupled with serological proteome analysis (SERPA) of the TAA repertoire of patients with thyroid encapsulated follicular-patterned/RAS-like phenotype (EFP/RLP) tumors. We identified several candidate cell-based (nicotinamide phosphoribosyltransferase NAMPT, glutamate dehydrogenase GLUD1, and glutathione S-transferase omega-1 GSTO1) and autoantibody (fumarate hydratase FH, calponin-3 CNN3, and pyruvate kinase PKM autoantibodies) biomarkers, including NRAS^Q61R-induced TAA phosphoglycerate kinase 1 PGK1. Meta-profiling of the reactivity of the identified autoantibodies across an independent SERPA series implicated the PKM autoantibody as a histological phenotype-independent biomarker of thyroid malignancy (11/38 (29%) patients with overtly malignant and uncertain malignant potential (UMP) tumors vs 0/22 (p = 0.0046) and 0/20 (p = 0.011) patients with non-invasive EFP/RLP tumors and healthy controls, respectively). PGK1 and CNN3 autoantibodies were identified as EFP/RLP-specific biomarkers, potentially suitable for further discriminating tumors with different malignant potential (PGK1: 7/22 (32%) patients with non-invasive EFP/RLP tumors vs 0/38 (p = 0.00044) and 0/20 (p = 0.0092) patients with other tumors and healthy controls, respectively; СNN3: 9/29 (31%) patients with malignant and borderline EFP/RLP tumors vs 0/31 (p = 0.00068) and 0/20 (p = 0.0067) patients with other tumors and healthy controls, respectively). The combined use of PKM, CNN3, and PGK1 autoantibodies allowed the reclassification of malignant/UMP tumor risk in 19/41 (46%) of EFP/RLP tumor patients. Taken together, we established an experimental pipeline DISER for the concurrent identification of cell-based and TAA biomarkers. The combination of DISER with in vitro oncogene expression allows further targeted identification of oncogene-induced TAAs. Using this integrated approach, we identified candidate autoantibody biomarkers that might be of value for differential diagnostic purposes in thyroid neoplasia.

Evaluation of the impact of cachexia on clinical outcomes in aggressive lymphoma

Cancer cachexia is a state of involuntary weight loss and altered body composition triggered by an underlying malignancy. We sought to correlate measures of cachexia with clinical outcomes in aggressive lymphomas and to identify biological pathways involved in the cachexia phenotype for possible druggable targets. Radiographic measures of cachexia were collected in a retrospective cohort of 109 patients with aggressive B-cell lymphoma and followed for clinical outcome. We found males with sarcopenia had reduced progression-free survival (5·4 vs. 72·3 months, P < 0·0005) and overall survival (OS; 30·2 months vs. not reached, NR, P = 0·02); males with adipopenia also had decreased OS (21·6 months vs. NR, P = 0·04). A trend for increased OS was observed in female sarcopenics only (32·8 months vs. NR, P = 0·08). Additionally, we analysed a prospective cohort of 14 patients for differences in circulating molecular targets involved in various biological pathways. There was a significant correlation with cachexia for reduced serum levels of mediators within the glucose utilization [insulin -like growth factor (IGF)-binding protein 6, P = 0·04; IGF-1, P = 0·02], inflammation (lymphotoxin-like inducible protein that competes with glycoprotein D for herpesvirus entry on T cells; LIGHT, P = 0·005), and energy intake/expenditure (leptin, P = 0·004). We conclude that cachexia in patients with aggressive lymphomas has sex-specific prognostic utility and correlates with measurable changes in metabolism and immune function.

Proteomics biomarkers for solid tumors: Current status and future prospects

Cancer is a heterogeneous multifactorial disease, which continues to be one of the main causes of death worldwide. Despite the extensive efforts for establishing accurate diagnostic assays and efficient therapeutic schemes, disease prevalence is on the rise, in part, however, also due to improved early detection. For years, studies were focused on genomics and transcriptomics, aiming at the discovery of new tests with diagnostic or prognostic potential. However, cancer phenotypic characteristics seem most likely to be a direct reflection of changes in protein metabolism and function, which are also the targets of most drugs. Investigations at the protein level are therefore advantageous particularly in the case of in-depth characterization of tumor progression and invasiveness. Innovative high-throughput proteomic technologies are available to accurately evaluate cancer formation and progression and to investigate the functional role of key proteins in cancer. Employing these new highly sensitive proteomic technologies, cancer biomarkers may be detectable that contribute to diagnosis and guide curative treatment when still possible. In this review, the recent advances in proteomic biomarker research in cancer are outlined, with special emphasis placed on the identification of diagnostic and prognostic biomarkers for solid tumors. In view of the increasing number of screening programs and clinical trials investigating new treatment options, we discuss the molecular connections of the biomarkers as well as their potential as clinically useful tools for diagnosis, risk stratification and therapy monitoring of solid tumors.

Lung cancer risk stratification using methylation profile in the oral epithelium

BACKGROUND

Assuming that the entire airway is affected by the same inhaled carcinogen, similar molecular alterations may occur in the lung and oral cavity. Thus, we hypothesized that DNA methylation profiles in the oral epithelium may be a promising biomarker for lung cancer risk stratification.

METHODS

A methylation-specific polymerase chain reaction was performed on oral epithelium from 16 patients with lung cancer and 32 controls without lung cancer. Genes showing aberrant methylation profiles in the oral epithelium were compared between patients and controls.

RESULTS

The analysis revealed that HOXD11 and PCDHGB6 were methylated more frequently in patients than in controls ( p = 0.0055 and p = 0.0247, respectively). Combined analyses indicated that 8 of 16 (50%) patients and 3 of 32 (9.4%) controls showed DNA methylation in both genes ( p = 0.0016). Among the population limited to current and former smokers, 6 of 11 (54.5%) patients showed methylation in both genes, compared to 1 of 17 (5.9%) controls ( p = 0.0037). In a subgroup analysis limited to the population above 50-years old, 8 of 16 (50%) patients and 2 of 16 (12.5%) controls showed methylation in both genes ( p = 0.0221).

CONCLUSIONS

The results of this study indicate that specific gene methylation in the oral epithelium might be a promising biomarker for lung cancer risk assessment, especially among smokers. Risk stratification through the analysis of DNA methylation profiles in the oral epithelium may be a useful and less invasive first-step approach in an efficient two-step lung cancer screening strategy.

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.

Plasma anti-BIRC5 IgG may be a useful marker for evaluating the prognosis of nonsmall cell lung cancer

A recent study demonstrated that circulating levels of IgG antibodies against linear peptide antigens derived from baculoviral IAP repeat-containing protein 5 isoform 2 (BIRC5) and myc proto-oncogene protein (MYC) were significantly increased in nonsmall cell lung cancer (NSCLC). This study was undertaken to replicate this initial work in an independent sample. An enzyme-linked immunosorbent assay (ELISA) was developed in-house to examine plasma IgG antibodies for three linear peptide antigens derived from BIRC5a, BIRC5b, and MYC in 211 patients with NSCLC and 200 control subjects. A Mann-Whitney U-test demonstrated that plasma anti-BIRC5a IgG levels, but not anti-BIRC5b or anti-MYC IgG levels, were significantly higher in NSCLC patients than control subjects, especially in male patients. Both squamous cell cancer and adenocarcinoma showed increased anti-BIRC5a IgG levels, but the IgG levels were not found to be changed significantly in the early stage of NSCLC. Kaplan-Meier survival analysis showed that NSCLC patients with high anti-BIRC5b IgG levels had better prognosis and longer overall survival (OS) than patients with low anti-BIRC5b IgG levels, although this significant difference failed to survive the adjustment for age, gender, NSCLC stages, and types. Plasma anti-BIRC5a and MYC IgG levels did not show significant associations with OS. In conclusion, Plasma anti-BIRC5 IgG may be a useful marker for assessment of prognosis of NSCLC but not for early diagnosis of this malignancy.

Screening for early stage lung cancer and its correlation with lung nodule detection

Currently, the most effective way of reducing lung cancer mortality is early diagnosis of lung cancer. The National Lung Screening Trial has proved the efficacy of lung cancer screening using low-dose computed tomography to reduce lung cancer mortality. However, many questions remain surrounding lung cancer screening implementation, among which include how to select the optimal risk population, the personalized screening interval based different levels of risk, methods to improve diagnostic discrimination between malignant and benign disease in detected lung nodules, and the roles of biomolecular markers in stratifying risk and in guiding the management of indeterminate nodules. This review concentrates on the latest developments of lung cancer screening and provides an overview of the main unanswered questions on lung nodule detection.

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.

Elevated expression of MMP-2 and TIMP-2 cooperatively correlates with risk of lung cancer

Lung cancer is one of the most common form of malignant diseases and the leading cause of cancer-related mortality worldwide. It is reported that approximately two-thirds of lung cancer patients is the presence of advance disease at the time of diagnosis. Hence novel lung cancer diagnostic tests, which can be used to screen individuals at high risk, are required. In the derivation cohort, a total of 88 patients admitted into hospital with suspected lung cancer were included. Bronchial alveolar lavage fluid (BALF) and lung tissue samples were collected from included patients, and were analyzed for MMP-2 and TIMP-2 expression. The results showed a higher level of MMP-2 and TIMP-2 expression and secretion in airways of lung cancer patients than that of benign diseases. A statistically significant correlation was observed between MMP-2 and TIMP-2. In addition, a validation cohort involving 107 patients was conducted to confirm these results. Interesting, BALF MMP-2 and TIMP-2 showed a high sensitivity and specificity in predicting the malignant nature of pulmonary disease in both derivation cohort and validation cohort. The findings in this study suggested that elevated expression of MMP-2 and TIMP-2 cooperatively correlates with risk of lung cancer. Measurement of MMP-2 and TIMP-2 in BALF might be helpful for differential diagnosis of primary lung cancer.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

OBJECTIVES

Autoantibodies against tumor-associated antigens (TAAs) identified in patients with advanced lung cancer may be detected in subjects with early lung cancer or even predate the diagnosis. The purpose of this study is to address the temporal relationship between lung cancer development and serum autoantibody response.

MATERIALS AND METHODS

Two cohorts of patients with newly diagnosed lung cancer were included. The first cohort included 90 sera from patients with lung cancer (Stages I-III) and 89 normal control sera. In the second cohort, 93 serial serum samples from 25 patients with CT-scan screen-detected stage I lung cancer were collected before the diagnosis of lung cancer (average 32 months) and 56 controls were matched on age, gender, and smoking. Autoantibody levels were measured by immunoassay.

RESULTS

Measurement of autoantibodies against seven TAAs (14-3-3ζ, c-Myc, MDM2, NPM1, p16, p53 and cyclin B1) individually could discriminate lung cancer patients from normal individuals in the first cohort and the area under curve (AUC) was 0.863 based on a panel of seven autoantibodies, with sensitivity of 68.9% and specificity of 79.5%. Autoantibodies in serial pre-diagnostic serum samples against the same panel of seven TAAs were detected prior to lung cancer diagnosis with sensitivity of 76.0% and specificity of 73.2% (AUC) (95%CI): 0.885 (0.797-0.973)). Elevated autoantibody levels could be detected greater than four years prior to lung cancer diagnosis.

CONCLUSION

A panel of seven TAAs may enhance the early detection of lung cancer, consistent with a humoral immune response to TAAs that can be detected months to years prior to the diagnosis.

Serum CEACAM1 Level Is Associated with Diagnosis and Prognosis in Patients with Osteosarcoma

Carcinoembryonic antigen related cell adhesion molecule 1 (CEACAM1) is a trans-membrane multifunctional cell adhesion molecule associated with tumor cell proliferation, apoptosis, angiogenesis, invasion, and migration during tumor development. In the present study, we evaluated serum CEACAM1 level in osteosarcoma patients to explore its diagnostic and prognostic value for this particular malignancy. Sera from 113 patients with primary osteosarcoma, 98 patients with benign bone tumors and 126 healthy controls were obtained. Serum CEACAM1 level was measured with ELISA and correlation with clinicopathological characteristics was further analyzed. Receiver operating curves (ROC), Kaplan-Meier curves, and log-rank analyses as well as Cox proportional hazard models were used to evaluate diagnostic and prognostic significance. The results revealed that serum CEACAM1 level was significantly higher in osteosarcoma patients compared to benign bone tumors and healthy controls (455.2 ± 179.9 vs 287.4 ± 103.2, 260.8 ± 109.7 pg/ml, respectively). Osteosarcoma patients with larger tumors, later-tumor stages, low tumor grades, and distant metastases had much higher CEACAM1 compared to those with smaller tumors, earlier tumor stages, high tumor grades and non-distant metastases (P < 0.05 for all). Multivariate logistic regression analysis confirmed that high serum CEACAM1 level was an independent risk factor for distant metastases (OR = 3.02, 95%CI 1.65–4.17). To distinguish osteosarcoma patients from those with benign bone tumor and healthy controls, ROC/AUC analysis indicated an AUC of 0.81 (sensitivity 0.61; specificity 0.89) and an AUC of 0.77 (sensitivity 0.57; specificity 0.92), respectively. Osteosarcoma patients with higher CEACAM1 had relatively lower survival compared to those with low CEACAM1 (P < 0.01), and multivariate analyses for overall survival revealed that high serum CEACAM1 level was an independent prognostic factor for osteosarcoma (HR = 1.56, 95%CI 1.23–3.28). The present study suggested that elevated serum CEACAM1 level might be a novel diagnostic and prognostic biomarker for osteosarcoma patients.

Comparative Study of Autoantibody Responses between Lung Adenocarcinoma and Benign Pulmonary Nodules

INTRODUCTION

The reduction in lung cancer mortality associated with computed tomography (CT) screening has led to its increased use and a concomitant increase in the detection of benign pulmonary nodules. Many individuals found to have benign nodules undergo unnecessary, costly, and invasive procedures. Therefore, there is a need for companion diagnostics that stratify individuals with pulmonary nodules into high-risk or low-risk groups. Lung cancers can trigger host immune responses and elicit antibodies against tumor antigens. The identification of these autoantibodies (AAbs) and their corresponding antigens may expand our knowledge of cancer immunity, leading to early diagnosis or even benefiting immunotherapy. Previous studies were performed mostly in the context of comparing cancers and healthy (smoker) controls. We have performed one of the first studies to understand humoral immune response in patients with cancer, patients with benign nodules, and healthy smokers.

METHODS

We first profiled seroreactivity to 10,000 full-length human proteins in 40 patients with early-stage lung cancer and 40 smoker controls by using nucleic acid programmable protein arrays to identify candidate cancer-specific AAbs. Enzyme-linked immunosorbent assays of promising candidates were performed on 137 patients with lung cancer and 127 smoker controls, as well as on 170 subjects with benign pulmonary nodules.

RESULTS

From protein microarray screening experiments using a discovery set of 40 patients and 40 smoker controls, 17 antigens showing higher reactivity in lung cancer cases relative to the controls were subsequently selected for evaluation in a large sample set (n = 264) by using enzyme-linked immunosorbent assay. A five-AAb classifier (tetratricopeptide repeat domain 14 [TTC14], B-Raf proto-oncogene, serine/threonine kinase [BRAF], actin like 6B [ACTL6B], MORC family CW-type zinc finger 2 [MORC2], and cancer/testis antigen 1B [CTAG1B]) that can differentiate lung cancers from smoker controls with a sensitivity of 30% at 89% specificity was developed. We further tested AAb responses in subjects with CT-positive benign nodules (n = 170), and developed a five-AAb panel (keratin 8, type II, TTC14, Kruppel-like factor 8, BRAF, and tousled like kinase 1) with a sensitivity of 30% at 88% specificity. Interestingly, messenger RNA levels of six AAb targets (TTC14, BRAF, MORC family CW-type zinc finger 2, cancer/testis antigen 1B, keratin 8, type II, and tousled like kinase 1) were also found to increase in lung adenocarcinoma tissues based on The Cancer Genome Atlas data set.

CONCLUSION

We discovered AAbs associated with lung adenocaricnoma that have the potential to differentiate cancer from CT-positive benign diseases. We believe that these antibodies warrant future validation using a larger sample set and/or longitudinal samples individually or as a panel. They could potentially be part of companion molecular diagnostic modalities that will benefit subjects undergoing CT screening for lung cancer.

Survivin Autoantibodies Are Not Elevated in Lung Cancer When Assayed Controlling for Specificity and Smoking Status

The high mortality rate in lung cancer is largely attributable to late diagnosis. Case-control studies suggest that autoantibodies to the survivin protein are potential biomarkers for early diagnosis. We tested the hypothesis that sandwich ELISA can detect autoantibodies to survivin before radiologic diagnosis in patients with early-stage non-small cell lung cancer (NSCLC). Because previous studies assayed survivin autoantibodies with the direct antigen-coating ELISA (DAC-ELISA), we first compared that assay with the sandwich ELISA. Based on the more robust results from the sandwich ELISA, we used it to measure survivin autoantibodies in the serum of 100 individuals from a well-controlled population study [the Dutch-Belgian Lung Cancer Screening Trial (NELSON) trial] composed of current and former smokers (50 patients with NSCLC, both before and after diagnosis, and 50 matched, smoking-habit control subjects), and another 50 healthy nonsmoking control subjects. We found no difference in specific autoantibodies to survivin in NSCLC patients, although nonspecific median optical densities were 24% higher (P < 0.001) in both NSCLC patients and smokers, than in healthy nonsmokers. Finally, we confirmed the ELISA results with Western blot analysis of recombinant and endogenous survivin (HEK-293), which showed no anti-survivin reactivity in patient sera. We conclude that specific anti-survivin autoantibody reactivity is most likely not present in sera before or after diagnosis. Autoantibody studies benefit from a comparison to a well-controlled population, stratified for smoking habit.

Circulating Anti-Matrix Metalloproteinase-7 Antibodies May Be a Potential Biomarker for Oral Squamous Cell Carcinoma

PURPOSE

The present study was conducted to evaluate the diagnostic and prognostic values of serum autoantibody against matrix metalloproteinase-7 (MMP-7) in patients with oral squamous cell carcinoma (OSCC).

MATERIALS AND METHODS

Anti-MMP-7 antibodies were measured in sera from 204 patients with OSCC and 212 normal controls using enzyme-linked immunosorbent assay, and clinicopathologic characteristics were correlated. Prognostic consequence was assessed with Kaplan-Meier curve and log-rank tests using Cox proportional hazard models. To check whether anti-MMP-7 antibody was related to tumor associated antigen, real-time polymerase chain reaction and western blot were used to measure MMP-7 mRNA and protein expression in tumor tissues from all 204 patients with OSCC.

RESULTS

Serum anti-MMP-7 antibody was higher in patients with OSCC (P < .05), and those with poorly differentiated tumors had more anti-MMP-7 antibody than those with well to moderate tumor differentiation (P < .01, P < .01, respectively). Patients with OSCC at late TNM stages (III, IV) and lymph node metastases had relatively higher serum anti-MMP-7 antibody levels than those with earlier stages (I, II) and those who lacked lymph node metastases (P < .05 for the 2 comparisons). OSCC prediction sensitivity as measured by receiver operating characteristics analysis was 0.485 and specificity was 0.896 (area under the curve, 0.761; 95% confidence interval, 0.716 to 0.806). Cox analysis showed that serum anti-MMP-7 antibody positivity independently predicted poor overall survival in patients with OSCC (hazard ratio, 1.82; 95% confidence interval, 1.07 to 4.61). MMP-7 mRNA and protein expression was increased in tumor tissues from patients with OSCC and high serum anti-MMP-7 antibody.

CONCLUSION

Serum anti-MMP-7 antibody might be a novel diagnostic and prognostic biomarker for OSCC.

Early detection of breast cancer using total biochemical analysis of peripheral blood components: a preliminary study

Background

Most of the blood tests aiming for breast cancer screening rely on quantification of a single or few biomarkers. The aim of this study was to evaluate the feasibility of detecting breast cancer by analyzing the total biochemical composition of plasma as well as peripheral blood mononuclear cells (PBMCs) using infrared spectroscopy.

Methods

Blood was collected from 29 patients with confirmed breast cancer and 30 controls with benign or no breast tumors, undergoing screening for breast cancer. PBMCs and plasma were isolated and dried on a zinc selenide slide and measured under a Fourier transform infrared (FTIR) microscope to obtain their infrared absorption spectra. Differences in the spectra of PBMCs and plasma between the groups were analyzed as well as the specific influence of the relevant pathological characteristics of the cancer patients.

Results

Several bands in the FTIR spectra of both blood components significantly distinguished patients with and without cancer. Employing feature extraction with quadratic discriminant analysis, a sensitivity of ~90 % and a specificity of ~80 % for breast cancer detection was achieved. These results were confirmed by Monte Carlo cross-validation. Further analysis of the cancer group revealed an influence of several clinical parameters, such as the involvement of lymph nodes, on the infrared spectra, with each blood component affected by different parameters.

Conclusion

The present preliminary study suggests that FTIR spectroscopy of PBMCs and plasma is a potentially feasible and efficient tool for the early detection of breast neoplasms. An important application of our study is the distinction between benign lesions (considered as part of the non-cancer group) and malignant tumors thus reducing false positive results at screening. Furthermore, the correlation of specific spectral changes with clinical parameters of cancer patients indicates for possible contribution to diagnosis and prognosis.

Epidemiologic design and analysis for proteomic studies: a primer on -omic technologies

Proteome analysis is increasingly being used in investigations elucidating the molecular basis of disease, identifying diagnostic and prognostic markers, and ultimately improving patient care. We appraised the current status of proteomic investigations using human samples, including the state of the art in proteomic technologies, from sample preparation to data evaluation approaches, as well as key epidemiologic, statistical, and translational issues. We systematically reviewed the most highly cited clinical proteomic studies published between January 2009 and March 2014 that included a minimum of 100 samples, as well as strategies that have been successfully implemented to enhance the translational relevance of proteomic investigations. Limited comparability between studies and lack of specification of biomarker context of use are frequently observed. Nevertheless, there are initial examples of successful biomarker discovery in cross-sectional studies followed by validation in high-risk longitudinal cohorts. Translational potential is currently hindered, as limitations in proteomic investigations are not accounted for. Interdisciplinary communication between proteomics experts, basic researchers, epidemiologists, and clinicians, an orchestrated assimilation of required resources, and a more systematic translational outlook for accumulation of evidence may augment the public health impact of proteomic investigations.

RNA-Seq and Network Analysis Revealed Interacting Pathways in TGF-β-Treated Lung Cancer Cell Lines

Whole transcriptome shotgun sequencing (RNA-Seq) is a useful tool for analyzing the transcriptome of a biological sample. With appropriate statistical and bioinformatic processing, this platform is capable of identifying significant differences in gene expression within the transcriptome and permits pathway and network analyses to determine how these genes interact biologically. In this study, we examined gene expression in two lung adenocarcinoma cell lines (H358 and A459) that were treated with transforming growth factor-β (TGF-β) as a model for induction of the epithelial-to-mesenchymal transition (EMT), commonly associated with disease progression. We performed this study in order to illustrate a workflow for identifying interesting genes and processes that are regulated early in EMT and to determine their gene pathway/network relationships and regulation. With this, we identified 137 upregulated and 32 downregulated genes common to both cell lines after TGF-β treatment that represent components of multiple canonical pathways and biological networks associated with the induction of EMT. These findings were also verified against reposited Affymetrix U133a expression profiles from multiple trials examining metastatic progression in patient cohorts (n = 731 total) to further establish the clinical relevance and translational significance of the model system. Together, these findings help validate the relevance of the TGF-β model for the study of EMT and provide new insights into early events in EMT.

Performance of a multiplexed dual analyte immunoassay for the early detection of non-small cell lung cancer

OBJECTIVES

"PAULA's" test (Protein Assays Utilizing Lung cancer Analytes) is a novel multiplex immunoassay blood test that incorporates both tumor antigens and autoantibodies to determine the risk that lung cancer (LC) is present in individuals from a high-risk population. The test's performance characteristics were evaluated in a study using 380 retrospective clinical serum samples.

METHODS

PAULA's test is performed on the Luminex xMAP technology platform, and detects a panel of 3 tumor antigens (CEA, CA-125, and CYFRA 21-1) and 1 autoantibody marker (NY-ESO-1). A training set (n = 230) consisting of 115 confirmed diagnoses of non-small cell lung carcinoma (NSCLC) cases and 115 age- and smoking history-matched controls was used to develop the LC predictive model. Data from an independent matched validation set (n = 150) was then used to evaluate the model developed, and determine the ability of the test to distinguish NSCLC cases from controls.

RESULTS

The 4-biomarker panel was able to discriminate NSCLC cases from controls with 74% sensitivity, 80% specificity, and 0.81 AUC in the training set and with 77% sensitivity, 80% specificity, and 0.85 AUC in the independent validation set. The use of NY-ESO-1 autoantibodies substantially increased the overall sensitivity of NSCLC detection as compared to the 3 tumor markers alone. Overall, the multiplexed 4-biomarker panel assay demonstrated comparable performance to a previously employed 8-biomarker non-multiplexed assay.

CONCLUSIONS

These studies confirm the value of using a mixed panel of tumor antigens and autoantibodies in the early detection of NSCLC in high-risk individuals. The results demonstrate that the performance of PAULA's test makes it suitable for use as an aid to determine which high-risk patients need to be directed to appropriate noninvasive diagnostic follow-up testing, especially low-dose CT (LDCT).

Urinary protein biomarkers in the early detection of lung cancer

The early detection of lung cancer has the potential to greatly impact disease burden through the timely identification and treatment of affected individuals at a manageable stage of development. The insufficient specificity demonstrated by currently used screening and diagnostic techniques has led to intense investigation into biomarkers as diagnostic tools. Urine may represent a noninvasive alternative matrix for diagnostic biomarker development. We performed an analysis of 242 biomarkers in urines obtained from 83 patients with non-small cell lung carcinomas (NSCLC), 74 patients diagnosed with benign pulmonary conditions, and 77 healthy donors. A large number of significant alterations were observed between the NSCLC and control groups. A multivariate analysis identified a three-biomarker panel consisting of IGFBP-1, sIL-1Ra, CEACAM-1, which discriminated NSCLC from healthy controls with a sensitivity/specificity of 84/95 in an initial training set and 72/100 in an independent validation set. This panel performed well among multiple subtypes of NSCLC and early-stage disease but demonstrated only limited efficacy for the discrimination of NSCLC from benign controls and limited specificity for patients with several other cancers and tuberculosis. These findings demonstrate that urine biomarkers may provide screening and diagnostic properties which exceed those reported for serum biomarkers and approach a level necessary for further clinical development.

"Sentinel" circulating tumor cells allow early diagnosis of lung cancer in patients with chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a risk factor for lung cancer. Migration of circulating tumor cells (CTCs) into the blood stream is an early event that occurs during carcinogenesis. We aimed to examine the presence of CTCs in complement to CT-scan in COPD patients without clinically detectable lung cancer as a first step to identify a new marker for early lung cancer diagnosis. The presence of CTCs was examined by an ISET filtration-enrichment technique, for 245 subjects without cancer, including 168 (68.6%) COPD patients, and 77 subjects without COPD (31.4%), including 42 control smokers and 35 non-smoking healthy individuals. CTCs were identified by cytomorphological analysis and characterized by studying their expression of epithelial and mesenchymal markers. COPD patients were monitored annually by low-dose spiral CT. CTCs were detected in 3% of COPD patients (5 out of 168 patients). The annual surveillance of the CTC-positive COPD patients by CT-scan screening detected lung nodules 1 to 4 years after CTC detection, leading to prompt surgical resection and histopathological diagnosis of early-stage lung cancer. Follow-up of the 5 patients by CT-scan and ISET 12 month after surgery showed no tumor recurrence. CTCs detected in COPD patients had a heterogeneous expression of epithelial and mesenchymal markers, which was similar to the corresponding lung tumor phenotype. No CTCs were detected in control smoking and non-smoking healthy individuals. CTCs can be detected in patients with COPD without clinically detectable lung cancer. Monitoring “sentinel” CTC-positive COPD patients may allow early diagnosis of lung cancer.

Circulating angiogenesis biomarkers are associated with disease progression in lung adenocarcinoma

BACKGROUND

Dysregulation of angiogenesis is known to be associated with tumorigenesis and metastatic progression in multiple carcinomas. The aim of this study was to evaluate the prognostic value of circulating angiogenesis biomarkers in lung adenocarcinoma progression. For that, we hypothesize that circulating levels of biomarkers characteristic for discrete processes within angiogenesis are associated with specific phases of disease progression. Appreciation of these profiles may have important implications for disease detection and prognostication.

METHODS

Patients with lung adenocarcinoma enrolled in the study were grouped as follows: node negative (T1a-3N0M0; n = 69), node positive (T1a-4N1-2M0; n = 60), and disseminated disease (TxNxM1; n = 68). All serum specimens were assayed for 17 angiogenesis biomarkers on the Luminex platform and statistically evaluated by analysis of variance for median differences in biomarker concentration at distinct phases of disease progression and by log rank methods for associations with clinical outcome.

RESULTS

We found circulating hepatocyte growth factor, heparin-binding epidermal growth factor, epidermal growth factor, and vascular endothelial growth factor-C levels significantly elevated (p < 0.05) in patients with node positive versus node negative disease. Similarly, median serum concentrations of bone morphogenic protein-9, endoglin, fibroblast growth factor-1, fibroblast growth factor-2, interleukin-8, placental growth factor, vascular endothelial growth factor-C, and vascular endothelial growth factor-D were significantly (p < 0.05) higher in patients with disseminated disease than in patients with node positive disease. Five biomarkers total were strongly prognostic (p < 0.05) for overall survival in the node negative cohort.

CONCLUSIONS

Angiogenesis is a process central to lung adenocarcinoma progression. We describe the modulation in serum angiogenesis biomarker concentrations through the various phases of non-small cell lung cancer progression. Additional refinement efforts are under way to enhance test performance, followed by additional validation studies.

Use of autoantibodies to detect the onset of breast cancer

The widespread use of screening mammography has resulted in increased detection of early-stage breast disease, particularly for in situ carcinoma and early-stage breast cancer. However, the majority of women with abnormalities noted on screening mammograms are not diagnosed with cancer because of several factors, including radiologist assessment, patient age, breast density, malpractice concerns, and quality control procedures. Although magnetic resonance imaging is a highly sensitive detection tool that has become standard for women at very high risk of developing breast cancer, it lacks sufficient specificity and costeffectiveness for use as a general screening tool. Therefore, there is an important need to improve screening and diagnosis of early-invasive and noninvasive tumors, that is, in situ carcinoma. The great potential for molecular tools to improve breast cancer outcomes based on early diagnosis has driven the search for diagnostic biomarkers. Identification of tumor-specific markers capable of eliciting an immune response in the early stages of tumor development seems to provide an effective approach for early diagnosis. The aim of this review is to describe several autoantibodies identified during breast cancer diagnosis. We will focus on these molecules highlighted in the past two years and discuss the potential future use of autoantibodies as biomarkers of early-stage breast cancer.

Current status of circulating protein biomarkers to aid the early detection of lung cancer

ABSTRACT: 

Considerable efforts have been undertaken to produce an effective screening method to reduce lung cancer mortality. Imaging tools such as low-dose computed tomography has shown an increase in the detection of early disease and a reduction in the rate of death. This screening modality has, however, several limitations, such as overdiagnosis and a high rate of false positives. Therefore, new screening methods, such as the use of circulating protein biomarkers, have emerged as an option that could complement imaging studies. In this review, current imaging techniques applied to lung cancer screening protocols are presented, as well as up-to-date status of circulating protein biomarker panels that may improve lung cancer diagnosis. Additionally, diverse statistical and artificial intelligence tools applied to the design and optimization of these panels are discussed along with the presentation of two commercially available blood tests recently developed to help detect lung cancer early.

Development of a multiplex autoantibody test for detection of lung cancer

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

Serum-based protein biomarkers for detection of lung cancer

Lung cancer is one of the most common cancers in terms of both incidence and mortality.The major reasons for the increasing number of deaths from lung cancer are late detection and lack of effective therapies. To improve our understanding of lung cancer biology, there is urgent need for blood-based, non-invasive molecular tests to assist in its detection in a cost-effective manner at an early stage when curative interventions are still possible. Recent advances in proteomic technology have provided extensive, high throughput analytical tools for identification, characterization and functional studies of proteomes. Changes in protein expression patterns in response to stimuli can serve as indicators or biomarkers of biological and pathological processes as well as physiological and pharmacological responses to drug treatment, thus aiding in early diagnosis and prognosis of disease. However, only a few biomarkers have been approved by the FDA to date for screening and diagnostic purposes. This review provides a brief overview of currently available proteomic techniques, their applications and limitations and the current state of knowledge about important serum biomarkers in lung cancer and their potential value as prognostic and diagnostic tools.

Systematic review: serum autoantibodies in the early detection of gastric cancer

Antibodies against tumor-associated antigens have been found in serum of patients with various types of cancers and may serve as biomarkers for early detection of gastric cancer as well. This systematic review aims to give an overview about known autoantibodies and their diagnostic value in gastric cancer. We conducted a systematic literature search in two databases to identify studies which performed serological testing for autoantibodies in gastric cancer patients and controls. Data on study characteristics and results were extracted independently by two reviewers. Overall, 39 articles reporting the detection of 34 different autoantibodies met the inclusion criteria for this review. The most common antibody detection method was enzyme-linked immunosorbent assay and the most frequently assessed autoantibody was anti-p53, which was tested in 13 studies. Most antibodies were assessed in only one study and only few authors have evaluated the diagnostic value of combinations of multiple autoantibodies. For single autoantibodies, specificity was generally very high (median: 99.15%), but sensitivity was mostly rather low (median: 12.35%). For some autoantibody combinations, substantially higher sensitivity at reasonably high levels of specificity could be achieved. Development of extended and optimized multimarker panels of autoantibodies might be a promising approach for gastric cancer early detection.

Early lung cancer diagnosis by biosensors

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