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

Bioinspired rational spatial-arrangement of antigens enables the accurate and rapid detection of anti-p53 autoantibody

A highly sensitive antibody detection strategy is presented that leverages the rational spatial arrangement of antigens at the sensing interface. Specifically, we employed rigid benzene ring-based coupling agents, carefully controlling their density and orientation on the biosensing interface to establish a well-defined spatial arrangement of receptor molecules, thereby enhancing antibody binding efficiency. Additionally, we utilized Au-decorated MoS2 nanosheets as an effective electrode modification, which also function as contact points for regulating the coupling agents. By optimizing both the electrode materials and the spatial arrangement of receptor molecules, our strategy enabled the precise and rapid detection of anti-p53 autoantibodies (anti-p53aAbs) in spiked plasma samples, achieving a broad linear range from 0.05 to 10 ng/mL and a low detection limit of 16.67 pg/mL, surpassing the performance of most existing methods. Notably, we introduce a biomimetic strategy for the spatial arrangement of antigens, inspired by the bionic recognition mechanism. This design effectively reduces steric hindrance between antibody molecules, enhances binding efficiency, and provides a novel approach for the rapid and sensitive detection of macromolecules, such as antibodies.

Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer

Introduction

Tumor-associated antigens (TAA) are proteins expressed during the growth and development of tumor cells, and TAA autoantibodies (TAAbs) can be detected in the serum of lung cancer patients, which can be utilized in the early screening of lung cancer. Almost all the TAAbs applied for diagnosis are those elevated, however, there are still large numbers of autoantibodies detected to decrease in tumor serums, and their functions were rarely known. Diagnosing malignant small lung nodules (≤3cm) in CT scans remains a challenge in clinical practice.

Methods

In this study, we applied the HuProt array and the bioinformatics analysis to assess the diagnostic values of the decreased autoantibodies in lung cancers.

Results

In total, 15 types of decreased autoantibodies were identified, and 6 of them were constructed into a predictive model for early lung cancer, reaching a sensitivity of 76.19% and a specificity of 55.74%. We combined with 4 elevated TAAbs, the sensitivity and the specificity of the 10-marker model can attain 80.0% and 87.0%, respectively, which is higher than that of the commonly used 7-TAAbs model in diagnosis for early-stage lung cancer. Moreover, 5 of the decreased autoantibodies can also be applied for supervising bone metastasis in lung adenocarcinoma. A follow-up process for 13 patients diagnosed with early-stage lung cancer revealed that 10 of the 15 decreased autoantibodies would recover to a higher level after the tumor was resected. Bioinformatic analysis indicated that the 15 biomarkers were strongly correlated with the prognosis of lung cancer patients.

Conclusion

We confirmed the importance of the decreased autoantibodies in lung cancer, providing new diagnostic and therapeutic strategies.

Pulmonary Epithelium Cell Fate Determination: Chronic Obstructive Pulmonary Disease, Lung Cancer, or Both

The concurrence of chronic obstructive pulmonary disease (COPD) and lung cancer has been widely reported and extensively addressed by pulmonologists and oncologists. However, most studies have focused on shared risk factors, DNA damage pathways, immune microenvironments, inflammation, and imbalanced proteases/antiproteases. In the present review, we explore the association between COPD and lung cancer in terms of airway pluripotent cell fate determination and discuss the various cell types and signaling pathways involved in the maintenance of lung epithelium homeostasis and their involvement in the pathogenesis of co-occurring COPD and lung cancer.

[Application Research of Serum miR-4646-5p, miR-3654 Combined with Traditional Lung Cancer Tumor Markers in the Diagnosis of Lung Cancer in Xuanwei, Yunnan Province]

BACKGROUND

The incidence rate of lung cancer in Xuanwei has been continuously increasing in recent years, and it also features high incidence across all age groups and high mortality rates among female lung cancer patients. Therefore, the search for more stable biomarkers for the diagnosis of Xuanwei lung cancer holds tremendous clinical application prospects. This study aims to explore the clinical application value of these four microRNAs (miRNAs) individually and in combination with traditional lung cancer tumor markers in the detection and diagnosis of Xuanwei lung cancer.

METHODS

By detecting the expression levels of four miRNAs and five traditional lung cancer tumor markers in the serum of 45 Xuanwei lung cancer patients and healthy physical examination participants, the Logistic regression model was employed to comprehensively evaluate the sensitivity, specificity, diagnostic efficacy, and other relevant statistical indicators of the four miRNAs in the diagnosis of Xuanwei lung cancer.

RESULTS

Among the individual miRNAs, miR-4646-5p and miR-3654 showed significant differences in expression levels between the Xuanwei lung cancer group and the control group (P<0.05). miR-3654 demonstrated the best diagnostic performance with a sensitivity of 86.7%, specificity of 82.2%, and an area under the curve of 0.847. Combining miR-3654 with miR-4646-5p and carcinoembryonic antigen (CEA) resulted in the highest diagnostic efficacy for Xuanwei lung cancer, with a sensitivity of 73.3%, specificity of 93.3%, area under the curve of 0.901, and a positive predictive value of 91.7%.

CONCLUSIONS

Among the four miRNAs, serum miR-3654 exhibits the best diagnostic efficacy for Xuanwei lung cancer. Combined with miR-4646-5p and CEA, its diagnostic value for Xuanwei lung cancer can be effectively enhanced, making it a promising screening indicator for Xuanwei lung cancer.

AI-enhanced diagnostic model for pulmonary nodule classification

Background

The identification of benign and malignant pulmonary nodules (BPN and MPN) can significantly reduce mortality. However, a reliable and validated diagnostic model for clinical decision-making is still lacking.

Methods

Enzyme-linked immunosorbent assay and electro chemiluminescent immunoassay were utilized to determine the serum concentrations of 7AABs (p53, GAGE7, PGP9.5, CAGE, MAGEA1, SOX2, GBU4-5), and 4TTMs (CYFR21, CEA, NSE and SCC) in 260 participants (72 BPNs and 188 early-stage MPNs), respectively. The malignancy probability was calculated using Artificial intelligence pulmonary nodule auxiliary diagnosis system, or Mayo model. Along with age, sex, smoking history and nodule size, 18 variables were enrolled for model development. Baseline comparison, univariate ROC analysis, variable correlation analysis, lasso regression, univariate and stepwise logistic regression, and decision curve analysis (DCA) was used to reduce and screen variables. A nomogram and DCA were built for model construction and clinical use. Training (60%) and validation (40%) cohorts were used to for model validation.

Results

Age, CYFRA21_1, AI, PGP9.5, GAGE7, and GBU4_5 was screened out from 18 variables and utilized to establish the regression model for identifying BPN and early-stage MPN, as well as nomogram and DCA for clinical practical use. The AUC of the nomogram in the training and validation cohorts were 0.884 and 0.820, respectively. Moreover, the calibration curve showed high coherence between the predicted and actual probability.

Conclusion

This diagnostic model and DCA could provide evidence for upgrading or maintaining the current clinical decision based on malignancy probability stratification. It enables low and moderate risk or ambiguous patients to benefit from more precise clinical decision stratification, more timely detection of malignant nodules, and early treatment.

A Co-Reactive Immunosensor Based on Ti3C2Tx MXene@TiO2-MoS2 Hybrids Promoting luminol@Au@Ni-Co NCs Electrochemiluminescence for CYFRA 21-1 Detection

The construction of assays is capable of accurately detecting cytokeratin-19 (CYFRA 21-1), which is critical for the rapid diagnosis of nonsmall cell lung cancer. In this work, a novel electrochemiluminescence (ECL) immunosensor based on the co-reaction promotion of luminol@Au@Ni-Co nanocages (NCs) as ECL probe by Ti3C2Tx MXene@TiO2-MoS2 hybrids as co-reaction accelerator was proposed to detect CYFRA 21-1. Ni-Co NCs, as a derivative of Prussian blue analogs, can be loaded with large quantities of Au NPs, luminol, and CYFRA 21-1 secondary antibodies due to their high specific surface area. To further improve the sensitivity of the developed ECL immunosensor, Ti3C2Tx MXene@TiO2-MoS2 hybrids were prepared by in situ growth of TiO2 nanosheets on highly conductive Ti3C2Tx MXene, and MoS2 was homogeneously grown on Ti3C2Tx MXene@TiO2 surfaces by the hydrothermal method. Ti3C2Tx MXene@TiO2-MoS2 hybrids possess excellent catalytic performance on the electro-redox of H2O2 generating more O2·- and obtaining optimal ECL intensity of the luminol/H2O2 system. Under the appropriate experimental conditions, the quantitative detection range of CYFRA 21-1 was from 0.1 pg mL-1 to 100 ng mL-1, and the limit of detection (LOD) was 0.046 pg mL-1. The present sensor has a lower LOD with a wider linear range, which provides a new analytical assay for the early diagnosis of small-cell-type lung cancer labels.

Optical Nanobiosensor Based on Surface-Enhanced Raman Spectroscopy and Catalytic Hairpin Assembly for Early-Stage Lung Cancer Detection via Blood Circular RNA

Lung cancer has become the leading cause of cancer-related deaths globally. However, early detection of lung cancer remains challenging, resulting in poor outcomes for the patients. Herein, we developed an optical biosensor integrating surface-enhanced Raman spectroscopy (SERS) with a catalyzed hairpin assembly (CHA) to detect circular RNA (circRNA) associated with tumor formation and progression (circSATB2). The signals of the Raman reporter were considerably enhanced by generating abundant SERS "hot spots" with a core-shell nanoprobe and 2D SERS substrate with calibration capabilities. This approach enabled the sensitive (limit of detection: 0.766 fM) and reliable quantitative detection of the target circRNA. Further, we used the developed biosensor to detect the circRNA in human serum samples, revealing that patients with lung cancer had higher circRNA concentrations than healthy subjects. Moreover, we characterized the unique circRNA concentration profiles of the early stages (IA and IB) and subtypes (IA1, IA2, and IA3) of lung cancer. These results demonstrate the potential of the proposed optical sensing nanoplatform as a liquid biopsy and prognostic tool for the early screening of lung cancer.

Clonal redemption of B cells in cancer

Potentially self-reactive B cells constitute a large portion of the peripheral B cell repertoire in both mice and humans. Maintenance of autoreactive B cell populations could conceivably be detrimental to the host but their conservation throughout evolution suggests performance of a critical and beneficial immune function. We discuss herein how the process of clonal redemption may provide insight to preservation of an autoreactive B cell pool in the context of infection and autoimmunity. Clonal redemption refers to additional recombination or hypermutation events decreasing affinity for self-antigen, while increasing affinity for foreign antigens. We then review findings in murine models and human patients to consider whether clonal redemption may be able to provide tumor antigen-specific B cells and how this may or may not predispose patients to autoimmunity.