Compensated Interferometry Measures of CYFRA 21-1 Improve Diagnosis of Lung Cancer

Quantification of the lung cancer tumor marker CYFRA 21-1 using protein precipitation, immunoaffinity bottom-up LC-MS/MS

OBJECTIVES

Numerous studies have proven the potential of cytokeratin 19 fragment 21-1 (CYFRA 21-1) detection in the (early) diagnosis and treatment monitoring of non-small cell lung cancer (NSCLC). Conventional immunoassays for CYFRA 21-1 quantification are however prone to interferences and lack diagnostic sensitivity and standardization. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is an emerging approach based on a different, often superior, detection principle, which may improve the clinical applicability of CYFRA 21-1 in cancer diagnostics. Therefore, we developed and validated a protein precipitation, immunoaffinity (IA) LC-MS/MS assay for quantitative analysis of serum CYFRA 21-1.

METHODS

Selective sample preparation was performed using ammonium sulfate (AS) precipitation, IA purification, tryptic digestion and LC-MS/MS quantification using a signature peptide and isotopically labeled internal standard. The workflow was optimized and validated according to EMA guidelines and results were compared to a conventional immunoassay.

RESULTS

Significant interference effects were seen during IA purification, which were sufficiently solved by performing AS precipitation prior to IA purification. A linear calibration curve was obtained in the range of 1.0-100 ng/mL (R2=0.98). Accuracy and precision were well within acceptance criteria. In sera of patients suspected of lung cancer, the method showed good correlation with the immunoassay.

CONCLUSIONS

A robust AS precipitation-IA LC-MS/MS assay for the quantification of serum CYFRA 21-1 was developed. With this assay, the clinically added value of LC-MS/MS-based detection over immunoassays can be further explored.

Electric field-enhanced backscatter interferometry detection for capillary electrophoresis

Backscatter interferometry (BSI) is a refractive index (RI) detection method that is easily integrated with capillary electrophoresis (CE) and is capable of detecting species ranging from inorganic ions to proteins without additional labels or contrast agents. The BSI signal changes linearly with the square of the separation voltage which has been used to quantify sample injection, but has not been explored as a potential signal enhancement mechanism in CE. Here we develop a mathematical model that predicts a signal enhancement at high field strengths, where the BSI signal is dominated by the voltage dependent mechanism. This is confirmed in both simulation and experiment, which show that the analyte peak area grows linearly with separation voltage at high field strengths. This effect can be exploited by adjusting the background electrolyte (BGE) to increase the conductivity difference between the BGE and analyte zones, which is shown to improve BSI performance. We also show that this approach has utility in small bore capillaries where larger separation fields can be applied before excess Joule heating degrades the separation. Unlike other optical detection methods that generally degrade as the optical pathlength is reduced, the BSI signal-to-noise can improve in small bore capillaries as the larger separation fields enhance the signal.

Direct Binding Methods to Measure Receptor-Ligand Interactions

G-protein-coupled receptors (GPCRs) contribute to numerous physiological processes via complex network mechanisms. While indirect signaling assays (Ca2+ mobilization, cAMP production, and GTPγS binding) have been useful in identifying and characterizing downstream signaling mechanisms of GPCRs, these methods lack measurements of direct binding affinities, kinetics, binding specificity, and selectivity that are important parameters in GPCR drug discovery. In comparison to existing direct methods that use radio- or fluorescent labels, label-free techniques can closely emulate the native interactions around binding partners. Surface plasmon resonance (SPR) is a label-free technique that utilizes the refractive index (RI) property and is applied widely in quantitative GPCR-ligand binding kinetics measurement including small molecules screening. However, purified GPCRs are further embedded in a synthetic lipid environment which is immobilized through different tags to the SPR sensor surface, resulting in a non-native environment. Here, we introduced a methodology that also uses the RI property to measure binding interactions in a label-free, immobilization-free arrangement. The free-solution technique is successfully applied in quantifying the interaction of bioactive lipids to cognate lipid GPCRs, which is not purified but rather present in near-native conditions, i.e., in milieu of other cytoplasmic lipids and proteins. To further consider the wide applicability of these free-solution approaches in biomolecular interaction research, additional applications on a variety of receptor-ligand pairs are imperative.

Improving lung cancer diagnosis with cancer, fungal, and imaging biomarkers

OBJECTIVE

Indeterminate pulmonary nodules (IPNs) represent a significant diagnostic burden in health care. We aimed to compare a combination clinical prediction model (Mayo Clinic model), fungal (histoplasmosis serology), imaging (computed tomography [CT] radiomics), and cancer (high-sensitivity cytokeratin fraction 21; hsCYFRA 21-1) biomarker approach to a validated prediction model in diagnosing lung cancer.

METHODS

A prospective specimen collection, retrospective blinded evaluation study was performed in 3 independent cohorts with 6- to 30-mm IPNs (n = 281). Serum histoplasmosis immunoglobulin G and immunoglobulin M antibodies and hsCYFRA 21-1 levels were measured and a validated CT radiomic score was calculated. Multivariable logistic regression models were estimated with Mayo Clinic model variables, histoplasmosis antibody levels, CT radiomic score, and hsCYFRA 21-1. Diagnostic performance of the combination model was compared with that of the Mayo Clinic model. Bias-corrected clinical net reclassification index (cNRI) was used to estimate the clinical utility of a combination biomarker approach.

RESULTS

A total of 281 patients were included (111 from a histoplasmosis-endemic region). The combination biomarker model including the Mayo Clinic model score, histoplasmosis antibody levels, radiomics, and hsCYFRA 21-1 level showed improved diagnostic accuracy for IPNs compared with the Mayo Clinic model alone with an area under the receiver operating characteristics curve of 0.80 (95% CI, 0.76-0.84) versus 0.72 (95% CI, 0.66-0.78). Use of this combination model correctly reclassified intermediate risk IPNs into low- or high-risk category (cNRI benign = 0.11 and cNRI malignant = 0.16).

CONCLUSIONS

The addition of cancer, fungal, and imaging biomarkers improves the diagnostic accuracy for IPNs. Integrating a combination biomarker approach into the diagnostic algorithm of IPNs might decrease unnecessary invasive testing of benign nodules and reduce time to diagnosis for cancer.

Assay Performance of a Label-Free, Solution-Phase CYFRA 21-1 Determination

CYFRA 21.1, a cytokeratin fragment of epithelial origin, has long been a valuable blood-based biomarker. As with most biomarkers, the clinical diagnostic value of CYFRA 21.1 is dependent on the quantitative performance of the assay. Looking toward translation, it is shown here that a free-solution assay (FSA) coupled with a compensated interferometric reader (CIR) can be used to provide excellent analytical performance in quantifying CYFRA 21.1 in patient serum samples. This report focuses on the analytical performance of the high-sensitivity (hs)-CYFRA 21.1 assay in the context of quantifying the biomarker in two indeterminate pulmonary nodule (IPN) patient cohorts totaling 179 patients. Each of the ten assay calibrations consisted of 6 concentrations, each run as 7 replicates (e.g., 10 × 6 × 7 data points) and were performed on two different instruments by two different operators. Coefficients of variation (CVs) for the hs-CYFRA 21.1 analytical figures of merit, limit of quantification (LOQ) of ca. 60 pg/mL, B _max, initial slope, probe-target binding affinity, and reproducibility of quantifying an unknown were found to range from 2.5 to 8.3%. Our results demonstrate the excellent performance of our FSA-CIR hs-CYFRA 21-1 assay and a proof of concept for potentially redefining the performance characteristics of this existing important candidate biomarker.

Photoelectrochemical sandwich immunoassay of CYFRA21-1 based on In2O3/WO3 type-II heterojunction and CdS quantum dots-polydopamine nanospheres labeling

Using an In₂O₃/WO₃ type-II heterojunction modified fluorine-doped tin oxide (FTO) electrode as the photoanode and CdS quantum dots (QDs)-polydopamine nanospheres (PDA NSs) as the secondary antibody (Ab₂) label, the photoelectrochemistry (PEC) sandwich immunosensing of the lung cancer marker CYFRA21-1 was studied. WO₃ nanoplates were prepared by a hydrothermal method, In₂O₃ nanoporous spheres were prepared by a hydrothermal method followed by calcination, and the In₂O₃/WO₃ type-II heterojunction with high PEC activity was prepared by ultrasonic mixing and cast-coating. PDA NSs with a high surface area can be loaded with abundant Ab₂ molecules and many CdS QDs with an energy level well matched with the heterojunction, so the photocurrent signal can be amplified by the formation of a sandwich immunostructure. Through the simulation experiments of photoelectrode-modified chitosan films of varying thickness, the effective transport distance of photogenerated charges is preliminarily discussed. Under the optimized conditions, the photocurrent was linear with the common logarithm of CYFRA21-1 concentration from 100 fg mL^-1 to 50 ng mL^-1, with a limit of detection of 56 fg mL^-1 (S/N = 3). The immunoassay of CYFRA21-1 in human serum samples gave satisfactory recovery results.

The impact of the lung EDRN-CVC on Phase 1, 2, & 3 biomarker validation studies

The Early Detection Research Network’s (EDRN) purpose is to discover, develop and validate biomarkers and imaging methods to detect early-stage cancers or at-risk individuals. The EDRN is composed of sites that fall into four categories: Biomarker Developmental Laboratories (BDL), Biomarker Reference Laboratories (BRL), Clinical Validation Centers (CVC) and Data Management and Coordinating Centers. Each component has a crucial role to play within the mission of the EDRN. The primary role of the CVCs is to support biomarker developers through validation trials on promising biomarkers discovered by both EDRN and non-EDRN investigators. The second round of funding for the EDRN Lung CVC at Vanderbilt University Medical Center (VUMC) was funded in October 2016 and we intended to accomplish the three missions of the CVCs: To conduct innovative research on the validation of candidate biomarkers for early cancer detection and risk assessment of lung cancer in an observational study; to compare biomarker performance; and to serve as a resource center for collaborative research within the Network and partner with established EDRN BDLs and BRLs, new laboratories and industry partners. This report outlines the impact of the VUMC EDRN Lung CVC and describes the role in promoting and validating biological and imaging biomarkers.

A sandwiched photoelectrochemical biosensing platform for detecting Cytokeratin-19 fragments based on Ag2S-sensitized BiOI/Bi2S3 heterostructure amplified by sulfur and nitrogen co-doped carbon quantum dots

A sandwiched photoelectrochemical (PEC) immunosensor based on BiOI/Bi₂S₃/Ag₂S was designed for the quantitative detection of cytokeratin-19 fragments (CYFRA21-1) in serum. In this work, due to the intervention of the narrow band gap Bi₂S₃, the absorption of the light source by the BiOI/Bi₂S₃ heterostructure has been significantly enhanced. Meanwhile, the matched band structure of BiOI, Bi₂S₃ and Ag₂S promoted the rapid transfer of electrons between the conduction bands and effectively inhibited the recombination of electron-hole pairs, thus enhanced the photoelectric signals. Sulfur and nitrogen co-doped carbon quantum dots (S,N-CQDs) with up-conversion luminescence properties provided more light energy for the base materials. On the other hand, S,N-CQDs were combined with Ab₂ through polydopamine (PDA), as secondary antibody labels, further enhanced the sensitivity of the sensor. Herein, the linear range of the sensor was from 0.001 to 100 ng mL^-1 and the detection limit was 1.72 pg mL^-1. In addition, the sensor provides a feasible way for the detection of tumor markers due to its excellent selectivity, repeatability and good stability.

Electrochemical impedance analysis of the CYFRA 21-1 antigen based on doxorubicin-initiated ROP signal amplification

The electrochemical immunoassay based on the Dox–PCL–PEO copolymer has been firstly used in the detection of CYFRA 21-1.

Integrated Biomarkers for the Management of Indeterminate Pulmonary Nodules

Rationale: Patients with indeterminate pulmonary nodules (IPNs) at risk of cancer undergo high rates of invasive, costly, and morbid procedures. Objectives: To train and externally validate a risk prediction model that combined clinical, blood, and imaging biomarkers to improve the noninvasive management of IPNs. Methods: In this prospectively collected, retrospective blinded evaluation study, probability of cancer was calculated for 456 patient nodules using the Mayo Clinic model, and patients were categorized into low-, intermediate-, and high-risk groups. A combined biomarker model (CBM) including clinical variables, serum high sensitivity CYFRA 21-1 level, and a radiomic signature was trained in cohort 1 (n = 170) and validated in cohorts 2-4 (total n = 286). All patients were pooled to recalibrate the model for clinical implementation. The clinical utility of the CBM compared with current clinical care was evaluated in 2 cohorts. Measurements and Main Results: The CBM provided improved diagnostic accuracy over the Mayo Clinic model with an improvement in area under the curve of 0.124 (95% bootstrap confidence interval, 0.091-0.156; P < 2 × 10-16). Applying 10% and 70% risk thresholds resulted in a bias-corrected clinical reclassification index for cases and control subjects of 0.15 and 0.12, respectively. A clinical utility analysis of patient medical records estimated that a CBM-guided strategy would have reduced invasive procedures from 62.9% to 50.6% in the intermediate-risk benign population and shortened the median time to diagnosis of cancer from 60 to 21 days in intermediate-risk cancers. Conclusions: Integration of clinical, blood, and image biomarkers improves noninvasive diagnosis of patients with IPNs, potentially reducing the rate of unnecessary invasive procedures while shortening the time to diagnosis.

The diagnostic significance of 64-slice spiral CT combined with serological CA19-9, Bcl-2, CYFRA21-1 detection in thoracic esophageal carcinoma

BACKGROUND

To analyze the clinical value of multi-slice spiral computed tomography (MSCT) combined with carbohydrate antigen 19-9 (CA19-9), B-cell leukemia/lymphoma-2 protein (Bcl-2), and cytokeratin 19 fragment antigen 21-1 (CYFRA21-1) detection in the diagnosis of thoracic esophageal cancer.

METHODS

The clinical data of 74 patients with thoracic esophageal cancer admitted to the Dazu District People's Hospital in Chonqing, China, from December 2019 to December 2020 were collected (esophageal cancer group), and their computed tomography (CT) signs were analyzed. Another 55 healthy people who underwent physical examination during the same period in the hospital were selected for the healthy group. The serum levels of CA19-9, Bcl-2, and CYFRA21-1 in the different populations were compared, using the receiver operating characteristic (ROC) curve to analyze the value of MSCT combined with CA19-9, Bcl-2, and CYFRA21-1 detection in the diagnosis of thoracic esophageal cancer.

RESULTS

The serum levels of CA19-9, Bcl-2, and CYFRA21-1 in patients of the esophageal cancer group were significantly higher than those in the healthy group (P<0.05). The serum levels of CA19-9, Bcl-2, and CYFRA21-1 in patients with poorly differentiated, stage III-IV carcinoma and lymph node metastasis were significantly higher than in those patients with moderately well-differentiated, stage I-II carcinoma and no lymph node metastasis (P<0.05). The CT scans of patients in the esophageal cancer group showed esophageal walls with irregular, needle-shaped, circular, or localized eccentric thickening and narrowed lumens, which were dilated above the cancerous lesions. Some tumors compressed adjacent organs to deform and shift the organs, resulting in the disappearance of surrounding fat layers. Enhanced scans showed mild or moderate enhancement, with large-diameter lesions unable to enhance central, low-density, necrotic areas. The ROC curve showed that the area under the curve (AUC) and the sensitivity and specificity of MSCT combined with CA19-9, Bcl-2, and CYFRA21-1 detection were all higher than for esophageal lesions detected by individual indicators.

CONCLUSIONS

CA19-9, Bcl-2, and CYFRA21-1, which are abnormally expressed in patients with esophageal cancer, may be related to the occurrence and development of esophageal cancer. MSCT combined with CA19-9, Bcl-2, and CYFRA21-1 detection appears to enhance the diagnosis of esophageal cancer.

Facile Encapsulation of Iridium(III) Complexes in Apoferritin Nanocages as Promising Electrochemiluminescence Nanodots for Immunoassays

A class of water-soluble electrochemiluminescence (ECL) nanodots were prepared by encapsulating ECL-active iridium complexes into biocompatible horse spleen apoferritin (apoHSF) nanocages for immunoassays. The preparation feasibility was achieved based on the pH-induced disassembly/reassembly nature originated from apoHSF. Two iridium nanodots (1 and 2) with high ECL efficiency were separately prepared by directing the self-assembly of two water-insoluble luminescent complexes, Ir(ppy)₃ (ppy = 2-phenylpyridine) and Ir(ppy)₂(acac) (ppy = 2-phenylpyridine and acac = acetylacetonate), in the apoHSF cavity. Using tri-n-propylamine (TPrA) as a coreactant, the electrochemistry and "oxidative-reductive" ECL mechanisms for nanodots 1 and 2 were investigated, respectively. After demonstrating the spectroscopic property and relative ECL efficiency, the ECL emission of nanodots 1 and 2 quenched by TPrA^• radicals at high potential was further studied and circumvented by optimizing the potential range and TPrA concentration for generating strong and stable ECL emission in aqueous media. The well-inherited biological functions of apoHSF in nanodots allow the convenient external modification of an antibody to act as a signal probe, thus a versatile ECL immunoassay paradigm was established. Acceptable results from this assay enabled the rapid and accurate detection of biomarkers in real samples. The unprecedented use of apoHSF is feasible and applicable for water-insoluble iridium complexes to fabricate a wide variety of biocompatible ECL nanodots for potential bioanalysis.

A model based on the quantification of complement C4c, CYFRA 21-1 and CRP exhibits high specificity for the early diagnosis of lung cancer

Lung cancer screening detects early-stage cancers, but also a large number of benign nodules. Molecular markers can help in the lung cancer screening process by refining inclusion criteria or guiding the management of indeterminate pulmonary nodules. In this study, we developed a diagnostic model based on the quantification in plasma of complement-derived fragment C4c, cytokeratin fragment 21-1 (CYFRA 21-1) and C-reactive protein (CRP). The model was first validated in two independent cohorts, and showed a good diagnostic performance across a range of lung tumor types, emphasizing its high specificity and positive predictive value. We next tested its utility in two clinically relevant contexts: assessment of lung cancer risk and nodule malignancy. The scores derived from the model were associated with a significantly higher risk of having lung cancer in asymptomatic individuals enrolled in a computed tomography (CT)-screening program (OR = 1.89; 95% CI = 1.20-2.97). Our model also served to discriminate between benign and malignant pulmonary nodules (AUC: 0.86; 95% CI = 0.80-0.92) with very good specificity (92%). Moreover, the model performed better in combination with clinical factors, and may be used to reclassify patients with intermediate-risk indeterminate pulmonary nodules into patients who require a more aggressive work-up. In conclusion, we propose a new diagnostic biomarker panel that may dictate which incidental or screening-detected pulmonary nodules require a more active work-up.

Diagnostic potential of extracellular vesicle-associated microRNA-10b and tumor markers for lung adenocarcinoma

MicroRNAs (miRNAs/miRs) in extracellular vesicles (EVs) are potential diagnostic markers. The purpose of the present study was to investigate potential EV miRNA biomarkers for lung adenocarcinoma (LUAD). Potential miRNAs were identified by searching public databases and verified by examining clinical samples. The diagnostic value of EV-associated miR-10b, plasma miR-10b and tumor markers (TMs), including α-fetoprotein (AFP), neuron-specific enolase, carcinoembryonic antigen (CEA), cytokeratin 19 fragment 21-1 (CYFRA211), pro-gastrin-releasing-peptide, carbohydrate antigen (CA)125, CA153, CA199 and CA724, was evaluated via receiver operating characteristic curve analysis. By searching the Gene Expression Omnibus and The Cancer Genome Atlas databases, miR-10b was identified as a potential biomarker. The analysis of clinical samples suggested that EV-associated miR-10b from plasma was significantly differentially expressed between LUAD and control samples. EV-associated miR-10b could function as a diagnostic marker for LUAD, with an AUC of 0.998, which was higher than the AUCs for TMs such as AFP, CEA, CYFRA211, CA125, CA153, CA199, CA724, pro-gastrin-releasing-peptide and neuron-specific enolase. In conclusion, EV-associated miR-10b may be a potential diagnostic biomarker for LUAD that is superior to plasma miR-10b and TMs.

Deep Multi-path Network Integrating Incomplete Biomarker and Chest CT Data for Evaluating Lung Cancer Risk

Clinical data elements (CDEs) (e.g., age, smoking history), blood markers and chest computed tomography (CT) structural features have been regarded as effective means for assessing lung cancer risk. These independent variables can provide complementary information and we hypothesize that combining them will improve the prediction accuracy. In practice, not all patients have all these variables available. In this paper, we propose a new network design, termed as multi-path multi-modal missing network (M3Net), to integrate the multi-modal data (i.e., CDEs, biomarker and CT image) considering missing modality with multiple paths neural network. Each path learns discriminative features of one modality, and different modalities are fused in a second stage for an integrated prediction. The network can be trained end-to-end with both medical image features and CDEs/biomarkers, or make a prediction with single modality. We evaluate M3Net with datasets including three sites from the Consortium for Molecular and Cellular Characterization of Screen-Detected Lesions (MCL) project. Our method is cross validated within a cohort of 1291 subjects (383 subjects with complete CDEs/biomarkers and CT images), and externally validated with a cohort of 99 subjects (99 with complete CDEs/biomarkers and CT images). Both cross-validation and external-validation results show that combining multiple modality significantly improves the predicting performance of single modality. The results suggest that integrating subjects with missing either CDEs/biomarker or CT imaging features can contribute to the discriminatory power of our model (p < 0.05, bootstrap two-tailed test). In summary, the proposed M3Net framework provides an effective way to integrate image and non-image data in the context of missing information.

Ultrasensitive label-free detection for lung cancer CYFRA 21-1 DNA based on ring-opening polymerization

Cytokeratin fragment antigen 21-1 (CYFRA 21-1) DNA is perceived as sensitive tumor marker for the diagnosis of non-small cell lung cancer and other tumor. Herein, linear chain poly(ε-caprolactone) (PCL) synthesized by ring-opening polymerization is applied to ultrasensitive label-free electrochemical impedance detection system for CYFRA 21-1 DNA. First, thiolated peptide nucleic acid (PNA) is self-assembled into the Au electrode surface through the formation of Au-S bonds, allowing the PNA to act as biomolecular probe and form PNA/DNA heteroduplex with the target DNA via specific hybridization. Then, PCL is conjugated to the immobilized DNA on the electrode via "carboxylate-Zr⁴⁺-phosphate" bridges. Finally, the electrochemical response of modified PNA/DNA/Zr⁴⁺/PCL electrode is determined by electrochemical impedance method to quantify of CYFRA 21-1 DNA. Under optimal conditions, this method exhibits highly sensitivity with a broad linear range (0.1 fM - 1 nM) (R² = 0.995) and the limit of detection (LOD) is as low as 10.73 aM, which is equivalent to just 64 molecules in a 10 μL sample. What's more, the high selectivity, good anti-interference, label-free operation, and real-time monitoring in complex samples of the proposed strategy demonstrate its broad application for the early diagnosis and clinical monitoring.

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

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

Development of a prediction model with serum tumor markers to assess tumor metastasis in lung cancer

BACKGROUND

This study aimed to explore the possibility of serum tumor markers (TMs) combinations in assessing tumor metastasis in patients with lung cancer.

METHODS

We performed a retrospective analysis of 541 patients diagnosed with lung cancer between January 2016 and December 2017 at the Pneumology Department of Dazhou Central Hospital. Serum carcinoembryonic antigen (CEA), carbohydrate antigen (CA)125, CA153, CA199, CA724, cytokeratin 19 fragment (CYFRA), and neuron-specific enolase (NSE) levels were quantified in each patient at the time of lung cancer diagnosis. Metastasis was confirmed by computed tomography, and/or positron emission tomography, and/or surgery or other necessary methods. Receiver operating characteristic (ROC) curves and calibration curves were used to evaluate the performance of the model.

RESULTS

Of the 541 patients eligible for final analysis, 253 were detected with metastasis and 288 were detected without metastasis. Compared with those in nonmetastatic patients, the serum CEA, CA125, CA199, CA153, CYFRA, and NSE levels were notably higher in metastatic patients (P < .05). The ROC curve demonstrated that the CEA-CA125-CA199-CA153-CYFRA-NSE-CA724 combination based on the cut-off value had an optimal area under the curve and specificity in assessing tumor metastasis. The decision tree model is a convenient and valuable tool for guiding the appropriate application of our model to assess metastasis in lung cancer patients.

CONCLUSIONS

Our study suggested that the nomogram of the regression model is valuable for assessing tumor metastasis in newly diagnosed lung cancer patients before traditional standard methods are used. These findings could aid in the evaluation of metastasis in the clinic.

Unlabeled lysophosphatidic acid receptor binding in free solution as determined by a compensated interferometric reader

Native interactions between lysophospholipids (LPs) and their cognate LP receptors are difficult to measure because of lipophilicity and/or the adhesive properties of lipids, which contribute to high levels of nonspecific binding in cell membrane preparations. Here, we report development of a free-solution assay (FSA) where label-free LPs bind to their cognate G protein-coupled receptors (GPCRs), combined with a recently reported compensated interferometric reader (CIR) to quantify native binding interactions between receptors and ligands. As a test case, the binding parameters between lysophosphatidic acid (LPA) receptor 1 (LPA₁; one of six cognate LPA GPCRs) and LPA were determined. FSA-CIR detected specific binding through the simultaneous real-time comparison of bound versus unbound species by measuring the change in the solution dipole moment produced by binding-induced conformational and/or hydration changes. FSA-CIR identified K_D values for chemically distinct LPA species binding to human LPA₁ and required only a few nanograms of protein: 1-oleoyl (18:1; K_D = 2.08 ± 1.32 nM), 1-linoleoyl (18:2; K_D = 2.83 ± 1.64 nM), 1-arachidonoyl (20:4; K_D = 2.59 ± 0.481 nM), and 1-palmitoyl (16:0; K_D = 1.69 ± 0.1 nM) LPA. These K_D values compared favorably to those obtained using the previous generation back-scattering interferometry system, a chip-based technique with low-throughput and temperature sensitivity. In conclusion, FSA-CIR offers a new increased-throughput approach to assess quantitatively label-free lipid ligand-receptor binding, including nonactivating antagonist binding, under near-native 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.

Free Solution Assay Signal Modulation in Variable-Stem-Length Hairpin Aptamers

Interferometric measurements of free solution assays (FSAs) quantify changes in molecular conformation and hydration upon binding. Here, we demonstrate that aptamer probes designed to undergo varying levels of conformational change upon binding produce corresponding variations in FSA signals. A series of hairpin aptamers were synthesized for the small molecule (tenofovir) with identical loop regions that contain the binding pocket, with between 2 and 10 self-associating base pairings in the stem region. Aptamers selected for tenofovir showed a decrease in the FSA signal and binding affinity (increase in K _D) with increasing stem length. Thermodynamic calculations of the Gibbs free energy (ΔG) reported a decrease in ΔG with respect to a corresponding increase in the aptamer stem length. Collectively, these observations provide an expanded understanding of FSA and demonstrate the potential for the rational design of label-free aptamer beacons using FSA as readout.

Polysaccharide-enhanced ARGET ATRP signal amplification for ultrasensitive fluorescent detection of lung cancer CYFRA 21-1 DNA

An ultrasensitive fluorescence biosensor for detecting cytokeratin fragment antigen 21-1 (CYFRA 21-1) DNA of non-small cell lung carcinoma (NSCLC) is designed using polysaccharide and activator regenerated by electron transfer atom transfer radical polymerization (ARGET ATRP) signal amplification strategy. Thiolated peptide nucleic acid (PNA) is fixed on magnetic nanoparticles (MNPs) by a cross-linking agent and hybridized with CYFRA 21-1 DNA. Hyaluronic acid (HA) is linked to PNA/tDNA heteroduplexes in the form of carboxy-Zr⁴⁺-phosphate. Subsequently, multiple 2-bromo-2-methylpropionic acid (BMP) molecules are linked with HA to initiate ARGET ATRP reaction. Finally, a large number of fluorescein o-acrylate (FA) monomers are polymerized on the macro-initiators, and the fluorescence signal is significantly amplified. Under optimal conditions, this biosensor shows a significant linear correlation between the fluorescence intensity and logarithm of CYFRA 21-1 DNA concentration (0.1 fM to 0.1 nM), and the limit of detection is as low as 78 aM. Furthermore, the sensor has a good ability to detect CYFRA 21-1 DNA in serum samples and to recognize mismatched bases. It suggests that the strategy has broad application in early diagnosis by virtue of its high sensitivity and selectivity. Graphical abstract A novel and highly sensitive fluorescence biosensor for quantitatively detecting CYFRA 21-1 DNA via dual signal amplification of hyaluronic acid and ARGET ATRP reaction was developed. This proposed method has a low detection limit, wide detection range, high selectivity, and strong anti-interference.