Screening Of Autoantibodies To Lung Cancer-associated Antigens Based On HuProt Protein Microarray And Construction Of Diagnostic Models

Background and purposeThe morbidity and mortality of lung cancer（LC）rank ahead among all malignant tumors in China.Due to the lack of effective early diagnostic methods,its five-year survival rate was only 19.0%.Low-dose computed tomography（LDCT）screening in high-risk populations can reduce the mortality of LC compared with x-ray examination.Due to the false positive rate of LDCT,it brings a mental burden to patients.Therefore,it is very crucial to find a panel of effective and non-invasive biomarkers for the diagnosis of LC.Autoantibodies to tumor-associated antigens（TAAbs）,as a kind of potential biomarkers with a serials of advantages like stable and lasting in serum,were produced by immune responses which triggered by tumor associated antigens（TAAs）.The research is aimed to discover novel TAAbs and construct the model by combining with multiple biomarkers,and thereby contribute to the early diagnosis of LC and the discrimination between benign pulmonary nodules（BPN）patients and malignant pulmonary nodules（MPN）patients.Methods1.Identification of TAAs by Hu Prot ^TMprotein microarrayTen mixed LC serum samples and ten mixed normal control（NC）serum samples were used to discover novel TAAs through Hu Prot ^TMprotein microarray.The data of protein microarray was normalized by z-score.Multiple data analysis was applied to select the candidate TAAs.2.Validation of TAAbs against candidate TAAs in sera from LC and NC and construction of model for the diagnosis of LC（Validation stage 1）Enzyme-linked immunosorbent assay（ELISA）was used to detect the level of candidate TAAbs in sera from 212 LC patients and 212 NC.Operating characteristic curve（ROC）was used to evaluate the diagnostic ability of TAAbs.The TAAbs with the area under the ROC curve（AUC）>0.5 and P<0.05 were further analyzed.Logistic regression analysis was used to the construction of model with the significant TAAbs and CEA for the diagnosis of LC.Finally,the diagnostic value of this model was evaluated in discriminating LC patients with different clinical characteristic from NC.3.Validation of TAAbs in sera from MPN and BPN patients and the construction of model for the discrimination of pulmonary nodules（PN）（Validation stage 2）According to AUC>0.6 and P<0.05 in validation stage 1,the TAAbs which are higher expressed in LC patients were considered to further research.Sera from 210patients with pulmonary nodules（PN）which included 105 MPN patients and 105BPN patients were used to detect the level of TAAbs by ELISA.The TAAbs with the AUC>0.5 and P<0.05,CT indicators and traditional tumor serum biomarkers（CEA,CYFRA21-1 and CA125）were performed to build the differential diagnosis model between BPN and MPN patients by logistic regression analysis.Finally,the discrimination capability of the model was evaluated for discriminating MPN patients with different clinical characteristic from BPN patients4.Statistical analysisAll results were analyzed or visualized by SPSS 25.0,and Graph Pad Prism 8.0software.Non-parametric test was used to compare the levels of TAAbs between LC patients and NC,MPN patients and BPN patients.ROC analysis was performed to evaluate the capability of models in the diagnosis of LC and discrimination of PN.The OD value of each autoantibody that shows the highest sensitivity with more than90%specificity was defined as the cutoff.The cutoff of models was the predicted probability with maximum YI.The two-tailed P value<0.05 was statistically significant.Results1.182 TAAs were screened through protein microarray.Subsequently,11 TAAs（SARS,ZPR1,FAM131A,GGA3,PRKCZ,HDAC1,GOLPH3,NSG1,DAB1,CD84,EEA1）with FC>2,P<0.05 and positive ratio（LC-NC）≥60%were further validated.2.The level of 10 TAAbs（anti-SARS,anti-ZPR1,anti-FAM131A,anti-GGA3,anti-PRKCZ,anti-HDAC1,anti-GOLPH3,anti-NSG1,anti-CD84 and anti-EEA1）showed a significant difference between LC patients and NC（P<0.05）.Anti-CD84possessed the highest diagnostic ability with the AUC（95%CI）of 0.693（0.643-0.744）while anti-HDAC1 yielded the lowest diagnostic ability with the AUC（95%CI）of0.579（0.524-0.634）for LC.3.The AUC of the panel with 4TAAbs（anti-ZPR1,anti-PRKCZ,anti-NSG1 and anti-CD84）was 0.747（0.691-0.802）.When combined with CEA,the AUC of model increased to 0.813（0.762-0.864）with the sensitivity of 68.9%and specificity of83.8%.The diagnostic model owned a higher diagnostic ability in LC patients at advanced stage（AUC:0.840,95%CI:0.788-0.892）and with positive lymph node metastasis（LM+）（AUC:0.827,95%CI:0.769-0.885）than LC patients at early stage（AUC:0.695,95%CI:0.570-0.820）and with negative lymph node metastasis（LM-）（AUC:0.770,95%CI:0.677-0.863）.The model showed no significant difference in diagnosing NSCLC patients（AUC:0.818,95%CI:0.761-0.878）,SCLC patients（AUC:0.816,95%CI:0.718-0.915）,positive distant metastasis（DM+）patients（AUC:0.808,95%CI:0.740-0.872）and negative distant metastasis（DM-）patients（AUC:0.816,95%CI:0.742-0.890）from NC.4.Seven out of 10 TAAbs（anti-SARS,anti-FAM131A,anti-PRKCZ,anti-GOLPH3,anti-NSG1,anti-CD84,anti-EEA1）with AUC>0.6 and P<0.05 in validation stage 1 were selected to validate in sera from 210 PN patients in validation stage 2.The level of 5 TAAbs（anti-SARS,anti-GOLPH3,anti-NSG1,anti-CD84 and anti-EEA1）showed a significant difference in serum from BPN patients and MPN patients（P<0.05）.Anti-EEA1 has the highest diagnostic value with the AUC（95%CI）of 0.630（0.555-0.705）while anti-CD84 has the lowest diagnostic value with the AUC（95%CI）of 0.580（0.503-0.657）.5.The AUC of model established by logistic regression with anti-EEA1,CEA,CYFRA21-1,CA125 and 3 CT indicators（vascular notch sign,lobulation sign,mediastinal lymph node enlargement）was 0.845 with the sensitivity of 58.3%and the specificity of 96.6%.The differential model showed a higher distinguishing ability in MPN patients at advanced stage（AUC:0.942,95%CI:0.893-0.990）,LM+patients（AUC:0.950,95%CI:0.910-0.999）and DM+patients（AUC:0.983,95%CI:0.952-1）than MPN patients at early stage（AUC:0.713,95%CI:0.592-0.834）,LM-MPN patients（AUC:0.683,95%CI:0.545-0.820）and DM-MPN patients（AUC:0.731,95%CI:0.615-0.848）.The AUC of patients with malignant nodules which are more than or equal to 3cm in diameter（AUC:0.938,95%CI:0.862-1）was higher than patients with malignant nodules which are less than 3 cm in diameter（AUC:0.808,95%CI:0.722-0.894）,which indicated that the model make a greater effect on discovering patients with malignant nodules which are more than or equal to 3cm in diameter.Conclusions1.Ten TAAbs（anti-SARS,anti-ZPR1,anti-FAM131A,anti-GGA3,anti-PRKCZ,anti-HDAC1,anti-GOLPH3,anti-NSG1,anti-CD84 and anti-EEA1）which were discovered through Hu Prot ^TMprotein microarray and validated by indirect ELISA maybe potential biomarkers for the diagnosis of lung cancer.Five out of 10 TAAbs（anti-SARS,anti-GOLPH3,anti-NSG1,anti-CD84 and anti-EEA1）could be potential biomarkers for differentiating BPN from MPN patients.2.The diagnostic model including 4 TAAbs（anti-ZPR1,anti-PRKCZ,anti-NSG1 and anti-CD84）and CEA owned a high diagnostic value for early lung cancer.3.The differential diagnosis model with anti-EEA1,3 CT indicators（vascular notch sign,lobulation sign,mediastinal lymph node enlargement）and CEA,CYFRA21-1,CA125 possessed a great effect on distinguishing BPN patients from MPN patients.