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

Autoantibodies in cancer: a systematic review of their clinical role in the most prevalent cancers

Although blood autoantibodies were initially associated with autoimmune diseases, multiple evidence have been accumulated showing their presence in many types of cancer. This has opened their use in clinics, since cancer autoantibodies might be useful for early detection, prognosis, and monitoring of cancer patients. In this review, we discuss the different techniques available for their discovery and validation. Additionally, we discuss here in detail those autoantibody panels verified in at least two different reports that should be more likely to be specific of each of the four most incident cancers. We also report the recent developed kits for breast and lung cancer detection mostly based on autoantibodies and the identification of novel therapeutic targets because of the screening of the cancer humoral immune response. Finally, we discuss unsolved issues that still need to be addressed for the implementation of cancer autoantibodies in clinical routine for cancer diagnosis, prognosis, and/or monitoring.

Development and validation of a TAAbs and TAAs based non-invasive model for diagnosing lung cancer

Background

Single Tumor-associated autoantibodies (TAAbs) and tumor-associated antigens (TAAs) have been found to have lower diagnostic efficacy in lung cancer. Our objective is to develop and validate a lung cancer prediction model that utilizes TAAbs and TAAs and to enhance the accuracy of lung cancer detection.

Methods

1830 subjects were randomly divided into training and validation sets at a 7:3 ratio for this study. Lasso regression analysis was used to remove collinear variables, whereas univariate logistic regression analysis was employed to identify potential independent risk factors for lung cancer. A diagnostic model was constructed using multivariate logistic analysis. The results were presented as a nomogram and assessed for various performance measures, including area under the curve, calibration curve, and decision curve analysis.

Results

The diagnostic model was developed using gender, age, GAGE7, MAGE-A1, CA125, and CEA as variables. The training set had an AUC of 0.787, while the validation set had an AUC of 0.750. The calibration curves of the training and validation sets showed a strong agreement between anticipated and observed values. The nomogram performed better than any individual variable in both the training and validation sets in terms of net benefits for lung cancer detection, according to DCA analysis.

Conclusions

This study proposes a diagnostic model for lung cancer that uses TAAbs and TAAs and incorporates individual characteristics. This model can be easily applied to personalized diagnosis.

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.

SERS sensing for cancer biomarker: Approaches and directions

These days, cancer is thought to be more than just one illness, with several complex subtypes that require different screening approaches. These subtypes can be distinguished by the distinct markings left by metabolites, proteins, miRNA, and DNA. Personalized illness management may be possible if cancer is categorized according to its biomarkers. In order to stop cancer from spreading and posing a significant risk to patient survival, early detection and prompt treatment are essential. Traditional cancer screening techniques are tedious, time-consuming, and require expert personnel for analysis. This has led scientists to reevaluate screening methodologies and make use of emerging technologies to achieve better results. Using time and money saving techniques, these methodologies integrate the procedures from sample preparation to detection in small devices with high accuracy and sensitivity. With its proven potential for biomedical use, surface-enhanced Raman scattering (SERS) has been widely used in biosensing applications, particularly in biomarker identification. Consideration was given especially to the potential of SERS as a portable clinical diagnostic tool. The approaches to SERS-based sensing technologies for both invasive and non-invasive samples are reviewed in this article, along with sample preparation techniques and obstacles. Aside from these significant constraints in the detection approach and techniques, the review also takes into account the complexity of biological fluids, the availability of biomarkers, and their sensitivity and selectivity, which are generally lowered. Massive ways to maintain sensing capabilities in clinical samples are being developed recently to get over this restriction. SERS is known to be a reliable diagnostic method for treatment judgments. Nonetheless, there is still room for advancement in terms of portability, creation of diagnostic apps, and interdisciplinary AI-based applications. Therefore, we will outline the current state of technological maturity for SERS-based cancer biomarker detection in this article. The review will meet the demand for reviewing various sample types (invasive and non-invasive) of cancer biomarkers and their detection using SERS. It will also shed light on the growing body of research on portable methods for clinical application and quick cancer detection.

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.

Clinical Value of Seven Autoantibodies Against Tumor-Associated Antigens and Tumor Markers in Lung Cancer Patients: A Retrospective Analysis from a Single Institution

Background: Lung cancer screening is not limited to low dose computed tomography (LDCT). Recently, molecular biomarkers have been shown to have the potential to improve the current state of early lung cancer detection. The current study determined the efficiency of seven autoantibodies against tumor-associated antigens (7-AABs) and tumor markers in patients with lung cancer. Materials and Methods: An enzyme-linked immunosorbent assay (ELISA) was used to determine the levels of 7-AABs and tumor markers in 354 patients with lung cancer and 108 patients with benign pulmonary disease under care at Ethics Committee of Tianjin Medical University General Hospital. Results: The sensitivity, specificity, positive predictive value (PPV), and area under the receiver operating characteristic (ROC) curve of 7-AABs were 30.0%, 84.3%, 86.3%, and 0.61, respectively. When combining the 7-AABs and tumor markers, the sensitivity was 68.6%, the specificity was 52.8%, and the area under the ROC curve was 0.72. The 7-AABs positive expression rate in lung cancer patients was significantly higher than patients with benign pulmonary diseases (30.1% vs 15.7%); however, the 7-AABs positive expression rate was affected by clinical features and pathologic stages. When combining 7-AABs and tumor markers, the combined 7-AABs and tumor marker positive expression rate increased to 68.6%. Conclusion: Based on this study and previous literature, the supplemental diagnostic value of 7-AABs has been confirmed; however, due to the low sensitivity, the value of 7-AABs alone in lung cancer screening is limited. The combination of 7-AABs and tumor markers has improved sensitivity and positivity, but decreased specificity, which makes their performance in cancer screening and early detection worthy of further research.

Novel Screening Tools for Lung Cancer

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

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.

Profiling Plasma Cytokines by A CRISPR-ELISA Assay for Early Detection of Lung Cancer

Cytokines play crucial roles in tumorigenesis and are potential biomarkers for cancer diagnosis. An Enzyme-linked Immunosorbent Assay (ELISA) is commonly used to measure cytokines but has a low sensitivity and can only detect a single target at a time. CRISPR-Associated Proteins (Cas) can ultra-sensitively and specifically detect nucleic acids and is revolutionizing molecular diagnostics. Here, we design a microplate-based CRISPR-ELISA assay to simultaneously profile multiple cytokines, in which antibodies are coupled with ssDNA to form antibody-ssDNA complexes that bridges CRISPR/Cas12a and ELISA reactions. The ssDNA triggers the Cas12a collateral cleavage activity and releases the fluorescent reporters to generate amplified fluorescent signals in the ELISA detection of cytokines. The CRISPR-ELISA assay can simultaneously measure multiple cytokines with a significantly higher sensitivity compared with conventional ELISA. Using the CRISPR-ELISA assay to profile plasma cytokines in 127 lung cancer patients and 125 cancer-free smokers, we develop a panel of plasma cytokine biomarkers (IL-6, IL-8, and IL-10) for early detection of the disease, with 80.6% sensitivity and 82.0% specificity. The CRISPR-ELISA assay may provide a new approach to the discovery of cytokine biomarkers for early lung cancer detection.

[Role and Significance of Bioactive Substances in Sputum in the Diagnosis of Lung Cancer]

肺癌是我国目前发病率最高的恶性肿瘤之一，其诊断的金标准需要进行组织活检的病理学检查或脱落细胞学检查，二者的有创性和敏感性限制了他们的使用。痰液中含有大量核酸、蛋白质，是肺功能的良好反映物，肺癌组织也会影响痰液中的生物成分，检测其中的生物活性物质可有助于肺癌的诊断。本文综合目前国内外的研究结果，对痰液中可用于肺癌诊断的生物活性物质做一综述。