A Diagnostic Model With IgM Autoantibodies and Carcinoembryonic Antigen for Early Detection of Lung Adenocarcinoma

Plasma IgG and IgM autoantibodies to COPT1 as potential biomarkers for detection of non-small cell lung cancer

Background

Early diagnosis of lung cancer is crucial for improving patient outcomes. Autoantibodies against tumor-associated antigens (TAAs) found in the plasma can serve as biomarkers for lung cancer detection. Copper transporter 1 (COPT1) is abnormally expressed in several cancers including lung cancer. The purpose of this study is to explore the significance of anti-COPT1 autoantibodies in the clinical diagnosis of non-small cell lung cancer (NSCLC).

Methods

The expression level of COPT1 in NSCLC and normal tissues was analyzed based on TCGA and the Human Protein Atlas (HPA) database. Through enzyme-linked immunosorbent assay (ELISA), the expression levels of anti-COPT1 autoantibodies in plasma samples from normal controls (NC), patients with benign pulmonary nodules (BPN), and patients with NSCLC were detected in the discovery (89 NC and 89 NSCLC) and verification (321 NC, 321 BPN and 321 NSCLC) groups. The ELISA results were verified by western blotting and indirect immunofluorescence experiments.

Results

Based on HPA and TCGA databases, the mRNA and protein levels of COPT1 were higher in NSCLC tissues than in normal tissues. The levels of anti-COPT1-IgG and anti-COPT1-IgM autoantibodies were significantly higher in patients with NSCLC (P<0.05). Anti-COPT1-IgG and anti-COPT1-IgM could discriminate NSCLC from NC with area under the curve (AUC) values of 0.733 (95% CI: 0.694-0.771) and 0.679 (95% CI: 0.638-0.720), respectively. Additionally, the combination of anti-COPT1-IgG, anti-COPT1-IgM, and carcinoembryonic antigen (CEA) could enhance the efficacy of NSCLC diagnosis from BPN with increased AUC values.

Conclusions

Our study indicated the potential significance of anti-COPT1-IgG and anti-COPT1-IgM autoantibodies as novel biomarkers for the detection of NSCLC. Furthermore, the combination of anti-COPT1-IgG and anti-COPT1-IgM improved the diagnostic value.

Plasma anti-PRTN3 IgG and IgM autoantibodies: novel biomarkers for early detection of lung adenocarcinoma

Background

Proteinase 3 (PRTN3) has been recognized as a crucial target for anti-neutrophil cytoplasmic autoantibody. However, the relationship between anti-PRTN3 autoantibody and cancer remains largely unexplored.

Methods

Immunohistochemistry was used to detect the level of PRTN3 in lung adenocarcinoma (LUAD) tissue array. Enzyme-linked immunosorbent assay was conducted to measure anti-PRTN3 IgG and IgM autoantibodies in plasma from patients with early- and advanced-stage LUAD, benign pulmonary nodules (BPN) and normal control (NC). Western blotting and immunofluorescence staining were performed to confirm the presence of plasma immune response to PRTN3.

Results

PRTN3 protein was highly expressed in LUAD tissues. Elevated plasma levels of anti-PRTN3 IgG and IgM autoantibodies were also detected in LUAD, especially in early LUAD. The AUC of anti-PRTN3 IgG autoantibodies in the diagnosis of early LUAD from NC was 0.782, and from BPN was 0.761. When CEA and anti-PRTN3 autoantibodies were combined, the AUC for the diagnosis of early LUAD was significantly higher than that of CEA alone. The presence of a plasma immune response to PRTN3 in LUAD was also confirmed.

Conclusion

Anti-PRTN3 IgG and IgM autoantibodies maybe early biomarkers to differentiate LUAD from NC and BPN.

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.

A Novel IgG-IgM Autoantibody Panel Enhances Detection of Early-stage Lung Adenocarcinoma from Benign Nodules

Autoantibodies hold promise for diagnosing lung cancer. However, their effectiveness in early-stage detection needs improvement. In this study, we investigated novel IgG and IgM autoantibodies for detecting early-stage lung adenocarcinoma (Early-LUAD) by employing a multi-step approach, including Human Proteome Microarray (HuProtTM) discovery, focused microarray verification, and ELISA validation, on 1246 individuals consisting of 634 patients with Early-LUAD (stage 0-I), 280 patients with benign lung disease (BLD), and 332 normal healthy controls (NHCs). HuProtTM selected 417 IgG/IgM candidates, and focused microarray further verified 55 significantly elevated IgG/IgM autoantibodies targeting 32 tumor-associated antigens in Early-LUAD compared to BLD/NHC/BLD+NHC. A novel panel of 10 autoantibodies (ELAVL4-IgM, GDA-IgM, GIMAP4-IgM, GIMAP4-IgG, MGMT-IgM, UCHL1-IgM, DCTPP1-IgM, KCMF1-IgM, UCHL1-IgG, and WWP2-IgM) demonstrated a sensitivity of 70.5% and a specificity of 77.0% or 80.0% for distinguishing Early-LUAD from BLD or NHC in ELISA validation. Positive predictive values for distinguishing Early-LUAD from BLD with nodules ≤ 8 mm, 9-20 mm, and > 20 mm significantly increased from 47.27%, 52.00%, and 62.90% [low-dose computed tomography (LDCT) alone] to 79.17%, 71.13%, and 87.88% (10-autoantibody panel combined with LDCT), respectively. The combined risk score (CRS), based on the 10-autoantibody panel, sex, and imaging maximum diameter, effectively stratified the risk for Early-LUAD. Individuals with 10 ≤ CRS ≤ 25 and CRS > 25 indicated a higher risk of Early-LUAD compared to the reference (CRS < 10), with adjusted odds ratios of 5.28 [95% confidence interval (CI): 3.18-8.76] and 9.05 (95% CI: 5.40-15.15), respectively. This novel panel of IgG and IgM autoantibodies offers a complementary approach to LDCT in distinguishing Early-LUAD from benign nodules.

Multisite DNA methylation alterations of peripheral blood mononuclear cells serve as novel biomarkers for the diagnosis of AIS/stage I lung adenocarcinoma: a multicenter cohort study

BACKGROUND

Early diagnosis remains an obstacle for improving the outcome of lung adenocarcinoma (LUAD). DNA methylation changes in peripheral blood mononuclear cells (PBMCs) could reflect an immune response to tumorigenesis, providing the theoretical basis for early cancer diagnosis based on immune cell profiling.

METHODS

This multi-center study evaluated the DNA methylation patterns based on PBMCs samples from 1115 individuals at nine medical centers. Genome-wide DNA methylation profiling of PBMCs in a discovery cohort (35 LUAD patients and 50 healthy controls) was performed using Illumina 850K microarray. Candidate differentially methylated CpG positions (DMPs) were selected and validated in a two-step DMPs screening cohort (65 LUAD patients and 80 healthy controls) by pyrosequencing and multiple target region methylation enrichment sequencing (MTRMES). Then, an early LUAD Diagnostic Panel (LDP score) based on multisite methylation-specific chip-based digital PCR was constructed in a training set and then confirmed in a validation set from the LDP score development cohort (389 AIS/stage I LUAD patients and 293 healthy controls). Besides, we included 157 other cancer patients, including 52 gastric cancer (GC) patients, 50 breast cancer (BC) patients, and 55 colorectal cancer (CRC) patients to assess the specificity of the LDP score. In addition, we also evaluated the early warning ability of LDP score for LUAD in a prospective cohort (46 people who were at high-risk of developing LC).

RESULTS

A total of 1415 LUAD-specific DMPs were identified. Then, six DMPs were selected for validation and three DMPs were finally verified. The LDP score was constructed by combining the three DMPs, age, and sex, and showed an AUC of 0.916, sensitivity of 88.17%, and specificity of 80.20% in a combined set, outperforming traditional methods, such as CEA and CT (detection rate: 87.79% vs. 4.69%; 87.79% vs. 35.21%). This diagnostic performance was confirmed in sub-types of LUAD with clinical challenges, such as 6-20 mm LUAD (AUC: 0.914, 95% CI: 0.889-0.934) and ground-glass nodules (AUC: 0.916, 95% CI: 0.889-0.938). Importantly, our LDP score had significant improvement in terms of selecting high-risk individuals who should receive low-dose computed tomography (87.80% vs. 9.28%). Remarkably, the LDP score could predict LUAD around 2 years before clinical diagnosis in our prospective cohort.

CONCLUSIONS

The novel developed LDP score represented a convenient and effective assay for the detection of AIS/stage I LUAD with high sensitivity and specificity, and had demonstrated unique advantages over traditional detection methods.

Smoking-induced CCNA2 expression promotes lung adenocarcinoma tumorigenesis by boosting AT2/AT2-like cell differentiation

Lung adenocarcinoma (LUAD), a type of non-small cell lung cancer (NSCLC), originates from not only bronchial epithelial cells but also alveolar type 2 (AT2) cells, which could differentiate into AT2-like cells. AT2-like cells function as cancer stem cells (CSCs) of LUAD tumorigenesis to give rise to adenocarcinoma. However, the mechanism underlying AT2 cell differentiation into AT2-like cells in LUAD remains unknown. We analyze genes differentially expressed and genes with significantly different survival curves in LUAD, and the combination of these two analyses yields 147 differential genes, in which 14 differentially expressed genes were enriched in cell cycle pathway. We next analyze the protein levels of these genes in LUAD and find that Cyclin-A2 (CCNA2) is closely associated with LUAD tumorigenesis. Unexpectedly, high CCNA2 expression in LUAD is restrictedly associated with smoking and independent of other driver mutations. Single-cell sequencing analyses reveal that CCNA2 is predominantly involved in AT2-like cell differentiation, while inhibition of CCNA2 significantly reverses smoking-induced AT2-like cell differentiation. Mechanistically, CCNA2 binding to CDK2 phosphorylates the AXIN1 complex, which in turn induces ubiquitination-dependent degradation of β-catenin and inhibits the WNT signaling pathway, thereby failing AT2 cell maintenance. These results uncover smoking-induced CCNA2 overexpression and subsequent WNT/β-catenin signaling inactivation as a hitherto uncharacterized mechanism controlling AT2 cell differentiation and LUAD tumorigenesis.

Humoral immune response to tumor-associated antigen Ubiquilin 1 (UBQLN1) and its tumor-promoting potential in lung cancer

BACKGROUND

This study aims to investigate the expression of UBQLN1 in lung cancer (LC) tissue and the diagnostic capability of autoantibody to UBQLN1 (anti-UBQLN1) in the detection of LC and the discrimination of pulmonary nodules (PNs).

METHODS

Sera from 798 participants were used to discover and validate the level of autoantibodies via HuProt microarray and Enzyme-linked immunosorbent assay (ELISA). Logistic regression analysis was applied to establish model. Receiver operating characteristic curve (ROC) analysis was performed to evaluate the diagnostic potential. Immunohistochemistry was performed to detect UBQLN1 expression in 88 LC tissues and 88 para-tumor tissues. qRT-PCR and western blotting were performed to detect the expression of UBQLN1 at the mRNA and protein levels, respectively. Trans-well assay and cell counting kit-8 (CCK-8) was used to investigate the function of UBQLN1.

RESULTS

Anti-UBQLN1 was identified with the highest fold change by protein microarray. The level of anti-UBQLN1 in LC patients was obviously higher than that in NC or patients with benign lung disease of validation cohort 1 (P<0.05). The area under the curve (AUC) of anti-UBQLN1 was 0.610 (95%CI: 0.508-0.713) while reached at 0.822 (95%CI: 0.784-0.897) when combining anti-UBQLN1 with CEA, CYFRA21-1, CA125 and three CT indicators (vascular notch sign, lobulation sign and mediastinal lymph node enlargement) in the discrimination of PNs. UBQLN1 protein was overexpressed in lung adenocarcinoma (LUAD) tissues compared to para-tumor tissues. UBQLN1 knockdown remarkably inhibited the migration, invasion and proliferation of LUAD cell lines.

CONCLUSIONS

Anti-UBQLN1 might be a potential biomarker for the diagnosis of LC and the discrimination of PNs.

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.

Effects of Oregano Essential Oil on IgA+, IgG+, and IgM+ Cells in the Jejunum of Castrated Holstein Bulls

The aim of this study was to investigate the effect of oregano essential oil on IgA+, IgG+, and IgM+ cells in the jejunum of castrated Holstein bulls. Twelve castrated Holstein bulls were randomly divided into control (YCK) and oregano essential oil (YEO) groups. Pathological changes in the jejunum were observed by HE staining, and the expression levels of IgA, IgG, and IgM in the jejunum were detected by ELISA. The distributions of IgA+, IgG+, and IgM+ cells in the jejunum were analysed by multiplex immunofluorescence and immunohistochemistry. The results showed that the jejunal villi were detached in the YCK group, which may have been related to inflammation, while the intestinal epithelium was clear and intact in the YEO group. The expressions of IgA, IgG, and IgM were significantly reduced by 40.75%, 30.76%, and 50.87%. The IgA+, IgG+, and IgM+ cells were diffusely distributed in the lamina propria of the jejunum, and were reduced by 17.07%, 6.44%, and 6.15%, respectively. Oregano essential oil did not alter the distribution characteristics of IgA+, IgG+, or IgM+ cells in the jejunum, but it suppressed inflammatory response, decreased immunoglobulin content, and significantly enhanced the formation of an immune barrier in the gastrointestinal mucosa.

Circulating autoantibodies to alpha-enolase (ENO1) and far upstream element-binding protein 1 (FUBP1) are negative prognostic factors for pancreatic cancer patient survival

Pancreatic ductal adenocarcinoma (PDA) has a dismal prognosis due to a lack of early diagnostic markers and effective therapy. In PDA patients, the glycolytic enzyme and plasminogen receptor alpha-enolase (ENO1) and the transcription factor far upstream element-binding protein 1 (FUBP1) are upregulated and elicit the production of autoantibodies (aAb) that discriminate healthy subjects from PDA patients, with the latter mostly directed to post-translational phosphorylated isoforms. Here, the correlation of prognosis with circulating ENO1 and FUBP1aAb, and their protein tissue expression was analyzed in PDA patients. Circulating ENO1 and FUBP1 aAb was analyzed in two cohorts of PDA patients by ELISA (n = 470), while tissues expression was observed by immunohistochemistry (n = 45). Overall survival (OS) was estimated using the Kaplan-Meier method, while the Cox model was used to estimate the hazard ratios (HR) adjusted for the main prognostic factors. Logistic models were applied to assess associations between death and its risk indicators. All statistical analyses were performed with Stata version 15. Unlike ENO1 aAb, there was a significant correlation between FUBP1 aAb and FUBP1 expression in tumors (p = 0.0268). In addition, we found that high ENO1 (p = 0.016) and intermediate FUBP1 aAb levels (p = 0.013) were unfavorable prognostic factors. Notably, it was found that high anti-FUBP1 aAb level is a good prognostic marker for tail-body PDA (p = 0.016). Our results suggest that different levels of circulating aAb to ENO1 and FUBP1 predict a poor outcome in PDA patients and can be used to improve therapeutic strategies.

The combination of circulating IgM and geriatric nutritional risk index predicts the prognostic of hepatocellular carcinoma patients who underwent immune checkpoint inhibitors

OBJECTIVE

Immune checkpoint inhibitors (ICIs) have shown promise in hepatocellular carcinoma (HCC) treatment. With the increasing use of ICIs in cancer treatment, identifying biomarkers that can predict the prognosis of patients receiving ICIs is of great importance. We aimed to investigate the potential of circulating immunoglobulins and the combination of Geriatric Nutritional Risk Index (GNRI) with IgM to predict prognosis in patients with HCC who received ICIs.

METHODS

Clinical and pathological data were collected from 101 patients with HCC who were administered ICIs and underwent circulating immunoglobulin testing between January 2018 and December 2021. Survival analysis, Cox regression analysis, and nomogram construction were performed to evaluate the prognostic value of the indicators.

RESULTS

In the preliminary survival analysis, we observed a significant correlation between patient prognosis and IgM levels. Patients with low IgM had shorter survival times. Upon combining the GNRI with IgM, patients with low GNRI and IgM levels had shorter progression-free survival (PFS) and overall survival (OS) (P < 0.001). Additionally, GNRI-IgM had the highest area under the curve (AUC) and was identified as an independent prognostic marker in this study. The C-indices of the nomograms for PFS and OS were 0.797 (0.734-0.860) and 0.827 (0.778-0.876), respectively.

CONCLUSIONS

IgM was significantly associated with the prognosis of patients with HCC receiving ICIs. The combination of the GNRI with IgM provided superior prognostic value and served as an independent prognostic marker. The GNRI-IgM can be used to effectively identify patients with HCC who are responsive to ICIs.

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.