The diagnostic value of a seven-autoantibody panel and a nomogram with a scoring table for predicting the risk of non-small-cell lung cancer

Clinical application of serum seven tumour-associated autoantibodies in patients with pulmonary nodules

Background

The incidence of pulmonary nodules is increasing because of the promotion and popularisation of low-dose computed tomography (LDCT) screening for populations with suspected lung cancer. However, a high rate of false positives and concerns regarding the radiation-related cancer risk of repeated CT scanning remain major obstacles to its wide application. This study aimed to investigate the clinical value of seven tumour-associated autoantibodies (7-TAAbs) in the differentiation of malignant pulmonary tumours from benign ones and the early detection of lung cancer in routine clinical practice.

Methods

We included 377 patients who underwent both the 7-TAAbs panel test and LDCT screening, and were diagnosed with pulmonary nodules using LDCT. An enzyme-linked immunosorbent assay (ELISA) was used to measure the serum levels antibodies for P53, PGP9.5, SOX2, GAGE7, GBU4-5, CAGE, and MAGE-A1. The relationships between the positive rates of the 7-TAAbs and the patient sex, and age, and the number, size, and composition of pulmonary nodules were analysed. We then statistically evaluated the clinical application value.

Results

The positive rates of the 7-TAAbs did not correlate with sex, age, number, size, or composition of pulmonary nodules. The serum antibody level of GBU4-5 in patients with pulmonary nodules tended to increase with age; the serum antibody level of SOX2 tended to increase with nodule size and was the highest among patients with mixed ground-glass opacity (mGGO) nodules. The antibody positive rate for CAGE in female patients with pulmonary nodules was significantly higher than that in male patients (P < 0.05). The positive rate of GBU4-5 antibody in patients aged 60 years and above was higher than that in younger patients (P < 0.05). The positive rate of GAGE7 antibody in patients with pulmonary nodules sized 8-20 mm was also significantly higher than that in patients with pulmonary nodules sized less than 8 mm (P < 0.01). Significant differences were observed in the GAGE7 antibody levels of patients with pulmonary nodules of different compositions (P < 0.01). The positive rate of the 7-TAAbs panel test in patients with lung cancer was significantly higher than in patients with pulmonary nodules (P < 0.01). Serum levels of P53, SOX2, GBU4-5, and MAGE-A1 antibodies were significantly higher in patients with lung cancer than in those with pulmonary nodules (P < 0.05).

Conclusion

The low positive rates of serum 7-TAAbs in patients with lung cancer and pulmonary nodules may be related to different case selection, population differences, geographical differences, different degrees of progression, and detection methods. The combined detection of 7-TAAbs has some clinical value for screening and early detection of lung cancer.

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

Objectives

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

Methods

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

Results

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

Conclusion

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

Improving the efficiency of identifying malignant pulmonary nodules before surgery via a combination of artificial intelligence CT image recognition and serum autoantibodies

OBJECTIVE

To construct a new pulmonary nodule diagnostic model with high diagnostic efficiency, non-invasive and simple to measure.

METHODS

This study included 424 patients with radioactive pulmonary nodules who underwent preoperative 7-autoantibody (7-AAB) panel testing, CT-based AI diagnosis, and pathological diagnosis by surgical resection. The patients were randomly divided into a training set (n = 212) and a validation set (n = 212). The nomogram was developed through forward stepwise logistic regression based on the predictive factors identified by univariate and multivariate analyses in the training set and was verified internally in the verification set.

RESULTS

A diagnostic nomogram was constructed based on the statistically significant variables of age as well as CT-based AI diagnostic, 7-AAB panel, and CEA test results. In the validation set, the sensitivity, specificity, positive predictive value, and AUC were 82.29%, 90.48%, 97.24%, and 0.899 (95%[CI], 0.851-0.936), respectively. The nomogram showed significantly higher sensitivity than the 7-AAB panel test result (82.29% vs. 35.88%, p < 0.001) and CEA (82.29% vs. 18.82%, p < 0.001); it also had a significantly higher specificity than AI diagnosis (90.48% vs. 69.04%, p = 0.022). For lesions with a diameter of ≤ 2 cm, the specificity of the Nomogram was higher than that of the AI diagnostic system (90.00% vs. 67.50%, p = 0.022).

CONCLUSIONS

Based on the combination of a 7-AAB panel, an AI diagnostic system, and other clinical features, our Nomogram demonstrated good diagnostic performance in distinguishing lung nodules, especially those with ≤ 2 cm diameters.

KEY POINTS

• A novel diagnostic model of lung nodules was constructed by combining high-specific tumor markers with a high-sensitivity artificial intelligence diagnostic system. • The diagnostic model has good diagnostic performance in distinguishing malignant and benign pulmonary nodules, especially for nodules smaller than 2 cm. • The diagnostic model can assist the clinical decision-making of pulmonary nodules, with the advantages of high diagnostic efficiency, noninvasive, and simple measurement.

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 combination of a seven-autoantibody panel with computed tomography scanning can enhance the diagnostic efficiency of non-small cell lung cancer

Background

Non-small cell lung cancer (NSCLC) is still of concern in differentiating it from benign disease. This study aims to validate the diagnostic efficacy of a novel seven-autoantibody (7-AAB) panel for the diagnosis of NSCLC.

Methods

We retrospectively enrolled 2650 patients who underwent both the 7-AAB panel test and CT scanning. We compared the sensitivity, specificity, and PPV of 7-AAB, CT, and PET-CT in the diagnosis of NSCLC in different subgroups. Then, we established a nomogram based on CT image features and the 7-AAB panel to further improve diagnostic efficiency. Moreover, we compared the pathological and molecular results of NSCLC patients in the 7-AABs positive group and the negative group to verify the prognostic value of the 7-AAB panel.

Results

The strategy of a “both-positive rule” combination of 7-AABs and CT had a specificity of 95.4% and a positive predictive value (PPV) of 95.8%, significantly higher than those of CT or PET-CT used alone (P&lt;0.05). The nomogram we established has passed the calibration test (P=0.987&gt;0.05) with an AUC of 0.791. Interestingly, it was found that the 7-AABs positive group was associated with higher proportion of EGFR mutations (P&lt;0.001), lower pathological differentiation degrees (P=0.018), more advanced pathological stages (P=0.040) and higher Ki-67 indexes (P=0.011) in patients with adenocarcinoma.

Conclusion

This study shows that combination of a 7-AAB panel with CT has can significantly enhance the diagnostic efficiency of lung cancer. Moreover, the 7-AAB panel also has potential prognostic value and has reference significance for the formulation of the treatment plan.

Plasma autoantibodies IgG and IgM to PD1/PDL1 as potential biomarkers and risk factors of lung cancer

Antibodies targeting programmed cell death-1 (PD1) and its ligand (PDL1) have transformed current cancer therapy while little is known about the expression of anti-PD1/PDL1 autoantibodies between lung cancer (LC) patients and normal controls (NC). The expression level of anti-PD1/PDL1 IgG and IgM was detected in plasma of 325 LC and 324 NC by indirect enzyme-linked immune sorbent assay (ELISA). Western blot and indirect immunofluorescence (IIF) were used to verify the ELISA results. The association analysis was used to evaluate the odds ratio (OR) of LC. The expression of anti-PD1/PDL1 IgG in LC samples was significantly higher than NC (P < 0.001 and P < 0.05, respectively). The positive rate of anti-PD1/PDL1 IgG in LC was significantly higher than NC and significant difference was also shown in LC samples of different clinical characteristics, such as clinical stage, nodules diameter, lymph node metastasis and distant metastasis (P < 0.001). Moreover, PD1/PDL1 expression in tissues showed no significant relation with that in plasma (P > 0.05). Anti-PD1/PDL1 IgG were the risk factors related to LC (OR (95% CI): 22.433 (5.426-92.745) and 5.051 (1.316-19.386)), while anti-PD1/PDL1 IgM were the risk factors for LC with ≤ 60 years (OR (95% CI): 6.122 (1.365-27.455) and 7.664 (1.715-34.251)) and anti-PD1 IgM was also the risk factor for male LC cases(OR (95% CI): 6.948 (1.076-44.868)). Plasma anti-PD1/PDL1 IgG and IgM might serve as potential biomarkers and risk predictors for LC.

Advances in lung cancer screening and early detection

Lung cancer is associated with a heavy cancer-related burden in terms of patients' physical and mental health worldwide. Two randomized controlled trials, the US-National Lung Screening Trial (NLST) and Nederlands-Leuvens Longkanker Screenings Onderzoek (NELSON), indicated that low-dose CT (LDCT) screening results in a statistically significant decrease in mortality in patients with lung cancer, LDCT has become the standard approach for lung cancer screening. However, many issues in lung cancer screening remain unresolved, such as the screening criteria, high false-positive rate, and radiation exposure. This review first summarizes recent studies on lung cancer screening from the US, Europe, and Asia, and discusses risk-based selection for screening and the related issues. Second, an overview of novel techniques for the differential diagnosis of pulmonary nodules, including artificial intelligence and molecular biomarker-based screening, is presented. Third, current explorations of strategies for suspected malignancy are summarized. Overall, this review aims to help clinicians understand recent progress in lung cancer screening and alleviate the burden of lung cancer.

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.

Detection of leucine-rich alpha-2-glycoprotein 1-containing immunocomplexes in the plasma of lung cancer patients with epitope-specific mAbs

BACKGROUND

Lung cancer is the leading cause of cancer-related deaths worldwide. With the expectation of improved survival, tremendous efforts and resources have been invested in the discovery of specific biomarkers for early detection of the disease. Several investigators have reported the presence of cancer-associated autoantibodies in the plasma or serum of lung cancer patients. Previously, we used a monoclonal-antibody proteomics technology platform for the discovery of novel lung cancer-associated proteins.

OBJECTIVE

The identification of specific protein epitopes associated with various cancers is a promising method in biomarker discovery. Here, in a preliminary study, we aimed to detect autoantibody-leucine-rich alpha-2-glycoprotein 1 (LRG1) immunocomplexes using epitope-specific monoclonal antibodies (mAbs).

METHODS

We performed sandwich ELISA assays using the LRG1 epitope-specific capture mAbs, Bsi0352 and Bsi0392, and an IgG-specific polyclonal antibody coupled to a reporter system as the detection reagent. We tested the plasma of lung-cancer patients and apparently healthy controls.

RESULTS

Depending on the epitope specificity of the capture monoclonal mAb, we were either unable to distinguish the control from LC-groups or showed a higher level of LRG1 and IgG autoantibody containing immunocomplexes in the plasma of non-small cell lung cancer and small cell lung cancer subgroups of lung cancer patients than in the plasma of control subjects.

CONCLUSIONS

Our findings underline the importance of protein epitope-specific antibody targeted approaches in biomarker research, as this may increase the accuracy of previously described tests, which will need further validation in large clinical cohorts.

Identification and Prognostic Value Exploration of Radiotherapy Sensitivity-Associated Genes in Non-Small-Cell Lung Cancer

Background

Non-small-cell lung cancer (NSCLC) is a prevalent malignancy with high mortality and poor prognosis. The radiotherapy is one of the most common treatments of NSCLC, and the radiotherapy sensitivity of patients could affect the individual prognosis of NSCLC. However, the prognostic signatures related to radiotherapy response still remain limited. Here, we explored the radiosensitivity-associated genes and constructed the prognostically predictive model of NSCLC cases.

Methods

The NSCLC samples with radiotherapy records were obtained from The Cancer Genome Atlas database, and the mRNA expression profiles of NSCLC patients from the GSE30219 and GSE31210 datasets were obtained from the Gene Expression Omnibus database. The Weighted Gene Coexpression Network Analysis (WGCNA), univariate, least absolute shrinkage and selection operator (LASSO), multivariate Cox regression analysis, and nomogram were conducted to identify and validate the radiotherapy sensitivity-related signature.

Results

WGCNA revealed that 365 genes were significantly correlated with radiotherapy response. LASSO Cox regression analysis identified 8 genes, including FOLR3, SLC6A11, ALPP, IGFN1, KCNJ12, RPS4XP22, HIST1H2BH, and BLACAT1. The overall survival (OS) of the low-risk group was better than that of the high-risk group separated by the Risk Score based on these 8 genes for the NSCLC patients. Furthermore, the immune infiltration analysis showed that monocytes and activated memory CD4 T cells had different relative proportions in the low-risk group compared with the high-risk group. The Risk Score was correlated with immune checkpoints, including CTLA4, PDL1, LAG3, and TIGIT.

Conclusion

We identified 365 genes potentially correlated with the radiotherapy response of NSCLC patients. The Risk Score model based on the identified 8 genes can predict the prognosis of NSCLC patients.

The role of seven autoantibodies in lung cancer diagnosis

Background

To investigate the expression and diagnostic value of seven autoantibodies (P53, PGP9.5, SOX2, GAGE7, GBU4-5, MAGE, and CACE) in lung cancer patients.

Methods

A total of 370 patients were admitted to the Thoracic Surgery of the First Affiliated Hospital of Suzhou University from 2017 to 2019, including 305 patients with lung cancer and 65 patients with benign lesions. The concentrations of the seven autoantibodies were determined by enzyme linked immunosorbent assay (ELISA).The expression levels of each antibody were compared between the two groups, and the levels of each antibody between lung cancer patients with different pathological types were also compared. We aimed to analyze the diagnostic efficiency of single antibody detection combined with seven antibodies, and also to explore whether there were differences among the positive rates of each antibody in sex, age, smoking history, pathological classification, and clinical stages in the lung cancer group.

Results

The expression levels of seven autoantibodies in the lung cancer group were higher than those in the benign lesion group. In the lung cancer group, the expression levels of the seven autoantibodies did not vary statistically among different pathological types. The area under the curve of combined detection of the seven antibodies reached 0.735, and the Y-index reached 0.35, which was higher than that of single antibody detection. P53 exhibited the highest sensitivity and lowest specificity; meanwhile, PGP9.5, SOX2, GAGE7, GBU4-5, and MAGEA1 exhibited low sensitivity and high specificity. The sensitivity and specificity of the CAGE were approximately 60%, respectively. There was no statistical difference in the positive rate of each antibody in age, smoking history, and clinical stage. The positive rate of MAGEA1 and CAGE was statistically different in sex, and the positive rate of MAGEA1 was statistically different in pathological classification.

Conclusions

The seven autoantibodies of lung cancer can potentially be used as an auxiliary examination method for the early diagnosis of lung cancer.

The diagnostic value of a seven-autoantibody panel and a nomogram with a scoring table for predicting the risk of non-small-cell lung cancer

The early detection of non-small-cell lung cancer (NSCLC) remains a common concern. The aim of our study was to validate the diagnostic value of a seven-autoantibody (7-AAB) panel compared with radiological diagnosis for NSCLC. We constructed a nomogram and a scoring table based on the 7-AAB panel's result to predict the risk of NSCLC. We prospectively enrolled 268 patients who presented with radiological lesions and underwent both the 7-AAB panel test and pathological diagnosis by surgical resection. A comparison between the 7-AAB panel and radiological diagnosis was performed. A nomogram and a scoring table based on the 7-AAB panel's result to predict the risk of NSCLC were constructed and internally validated. The 7-AAB panel test had a specificity of 90.2% and a positive predictive value (PPV) of 92.7%, which were significantly higher than those of the radiological diagnosis. The 7-AAB panel also showed a preferable sensitivity in patients with early-stage disease. Seven factors, including the 7-AAB panel results, were integrated into the nomogram. For more convenient application, we formulated a scoring table based on the nomogram. The area under the receiver operating characteristic curve was 0.840 and 0.860 in the training group and validation group, respectively, which was higher than that using the 7-AAB panel or radiological diagnosis alone. This study reveals that our 7-AAB panel has clinical value in the diagnosis of NSCLC. The utility of our nomogram and the scoring table indicated that they have the potential to assist clinicians in avoiding unnecessary treatment or needless follow-up.