Autoantibody signatures defined by serological proteome analysis in sera from patients with cholangiocarcinoma

Identification and validation of serum autoantibodies in children with B-cell acute lymphoblastic leukemia by serological proteome analysis

Background

B-cell acute lymphoblastic leukemia (B-ALL) is the most common malignancy of childhood. Even though significant progresses have been made in the treatment of B-ALL, some pediatric B-ALL have still poor prognosis. The identification of tumor autoantibodies may have utility in early cancer diagnosis and immunotherapy. In this study, we used serological proteome analysis (SERPA) to screen serum autoantibodies of pediatric B-ALL, aiming to contribute to the early detection of B-ALL in children.

Methods

The total proteins from three pooled B-ALL cell lines (NALM-6, REH and BALL-1 cells) were separated using two-dimensional gel electrophoresis (2-DE), which was followed by Western blot by mixed serum samples from children with B-ALL (n=20) or healthy controls (n=20). We analyzed the images of 2-D gel and Western blot by PDQuest software, and then identified the spots of immune responses in B-ALL samples compared with those in control samples. The proteins from spots were identified using mass spectrometry (MS). The autoantibodies against alpha-enolase (α-enolase) and voltage-dependent anion-selective channel protein 1 (VDAC1) were further validated in sera from another 30 children with B-ALL and 25 normal individuals by the use of enzyme-linked immunosorbent assay (ELISA). The protein expression levels of the candidate antigens α-enolase and VDAC1 in B-ALL were thoroughly studied by immunohistochemical analysis.

Results

Utilizing the SERPA approach, α-enolase and VDAC1 were identified as candidate autoantigens in children with B-ALL. The frequencies of autoantibodies against α-enolase and VDAC1 in children with B-ALL were 27% and 23% by using ELISA analysis, respectively, which were significantly higher than those in normal controls (4% and 0, p<0.05). Immunohistochemical analysis showed the expression of α-enolase and VDAC1 was positive in 95% and 85% of B-ALL patients, respectively, but negative expression levels were showed in the control group.

Conclusions

This study incidated that α-enolase and VDAC1 may be the autoantigens associated with B-ALL. Therefore, α-enolase and VDAC1 autoantibodies may be the potential serological markers for children with B-ALL.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12953-021-00184-w.

Using protein microarray to identify and evaluate autoantibodies to tumor-associated antigens in ovarian cancer

The aim of this study was to develop a noninvasive serological diagnostic approach in identifying and evaluating a panel of candidate autoantibodies to tumor‐associated antigens (TAAs) based on protein microarray technology for early detection of ovarian cancer (OC). Protein microarray based on 154 proteins encoded by 138 cancer driver genes was used to screen candidate anti‐TAA autoantibodies in a discovery cohort containing 17 OC and 27 normal controls (NC). Indirect enzyme‐linked immunosorbent assay (ELISA) was used to detect the content of candidate anti‐TAA autoantibodies in sera from 140 subjects in the training cohort. Differential anti‐TAA autoantibodies were further validated in the validation cohort with 328 subjects. Subsequently, 112 sera from the patients with ovarian benign diseases with 104 OC sera and 104 NC sera together were recruited to identify the specificity of representative autoantibodies to OC among ovarian diseases. Five TAAs (GNAS, NPM1, FUBP1, p53, and KRAS) were screened out in the discovery phase, in which four of them presented higher levels in OC than controls (P < .05) in the training cohort, which was consistent with the result in the subsequent validation cohort. An optimized panel of three anti‐TAA (GNAS, p53, and NPM1) autoantibodies was identified to have relatively high sensitivity (51.2%), specificity (86.0%), and accuracy (68.6%), respectively. This panel can identify 51% of OC patients with CA125 negative. This study supports our assumption that anti‐TAA autoantibodies can be considered as potential diagnostic biomarkers for detection of OC; especially a panel of three anti‐TAA autoantibodies could be a good tool in immunodiagnosis of OC.

Immunoproteomics approach revealed elevated autoantibody levels against ANXA1 in early stage gallbladder carcinoma

Background

Early diagnosis is important for the timely treatment of gallbladder carcinoma (GBC) patients and may lead to increased survival outcomes. Here, we have applied serological proteome analysis (SERPA), an immunoproteomics approach, for the detection of ‘tumor-associated antigens (TAAs) that elicit humoral response’ in early stage GBC patients.

Methods

Total protein from pooled tumor tissue of GBC patients (n = 7) was resolved by two-dimensional gel electrophoresis (2-DE) followed by immunoblotting using pooled blood plasma from healthy volunteers (n = 11) or gallstone disease (GSD) cases (n = 11) or early stage GBC (Stage I and II) (n = 5) or GBC stage IIIA (n = 9). 2-D gel and immunoblot images were acquired and analyzed using PDQuest software to identify immunoreactive spots in GBC cases in comparison to controls. Proteins from immunoreactive spots were identified by liquid chromatography- tandem mass spectrometric analysis (LC-MS/MS). Autoantibody levels for two of the functionally relevant proteins were investigated in individual plasma samples (52 cases and 89 controls) by dot blot assay using recombinant proteins.

Results

Image analysis using PDQuest software identified 25 protein spots with significantly high or specific immunoreactivity in GBC cases. Mass spectrometric analysis of 8 corresponding protein spots showing intense immunoreactivity (based on densitometric analysis) in early stage GBC or GBC stage IIIA cases led to the identification of 27 proteins. Some of the identified proteins include ANXA1, HSPD1, CA1, CA2, ALDOA and CTSD. Among the two proteins, namely ANXA1 and HSPD1 verified using a cohort of samples, significantly elevated autoantibody levels against ANXA1 were observed in early stage GBC cases in comparison to healthy volunteers or GSD cases (unpaired t-test, p < 0.05). Receiver operating characteristic (ROC) curve analysis for ANXA1 showed an Area under the Curve (AUC) of 0.69, with 41.7% sensitivity against a specificity of 89.9% for early stage GBC. IHC analysis for ANXA1 protein showed ‘high’ expression levels in 72% of GBC cases whereas all the controls showed ‘low’ expression levels.

Conclusions

The study suggests that the ANXA1 autoantibody levels against ANXA1 may be potentially employed for early stage detection of GBC patients. Other proteins could also be explored and verified in a large cohort of clinical samples.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-020-07676-6.

PulseDIA: Data-Independent Acquisition Mass Spectrometry Using Multi-Injection Pulsed Gas-Phase Fractionation

The performance of data-independent acquisition (DIA) mass spectrometry (MS) depends on the separation efficiency of peptide precursors. In Orbitrap-based mass spectrometers, separation efficiency of peptide precursors is limited by the relatively slow scanning rate compared to time of flight (TOF)-based MS. Here, we present PulseDIA, a multi-injection gas-phase fractionation (GPF) strategy for enhanced DIA-MS. This is achieved by equally dividing the conventional DIA analysis covering the entire mass range into multiple injections for DIA analyses with complementary windows. Using mouse liver digests, the PulseDIA method identified up to 50% more peptides and 29% more protein groups than that by conventional DIA with the same length of effective gradient time. Compared to conventional multi-injection GPF, PusleDIA exhibited higher flexibility and identified up to 18% more peptides and 8% more protein groups using two injections. The gain of peptides per effective time unit was the highest in PulseDIA compared to conventional DIA and GPF. We further applied the PulseDIA method to profile the proteome of 18 human tissue samples (benign and malignant) from nine cholangiocarcinoma (CCA) patients. PulseDIA identified 7796 protein groups in these CCA samples, with a 14% increase of protein group identification compared to the conventional DIA method. The missing value for protein matrix dropped by 7% using PulseDIA compared to DIA. A total of 681 significantly altered proteins were detected in CCA samples using PulseDIA, including several dysregulated proteins, which were absent in the conventional DIA analysis. Taken together, we present PulseDIA as an enhanced DIA-MS method with improved sensitivity and reproducibility.

Autoantigens in the trabecular meshwork and glaucoma-specific alterations in the natural autoantibody repertoire

OBJECTIVES

Primary open-angle glaucoma (POAG) is a neurodegenerative disorder leading to a gradual vision loss caused by progressive damage to the optic nerve. Immunological processes are proposed to be involved in POAG pathogenesis. Altered serological autoantibody levels have been frequently reported, but complete analyses of the natural autoantibodies with respect to disease-related alterations are scarce. Here, we provide an explorative analysis of pathways and biological processes that may involve naturally immunogenic proteins and highlight POAG-specific alterations.

METHODS

Mass spectrometry-based antibody-mediated identification of autoantigens (MS-AMIDA) was carried out in healthy and glaucomatous trabecular meshwork (TM) cell lines, using antibody pools purified from serum samples of 30 POAG patients and 30 non-glaucomatous subjects. Selected antigens were validated by protein microarray (n = 120). Bioinformatic assessment of identified autoantigens, including Gene Ontology (GO) enrichment analysis and protein-protein interaction networks, was applied.

RESULTS

Overall, we identified 106 potential autoantigens [false discovery rate (FDR) < 0.01], from which we considered 66 as physiological targets of natural autoantibodies. Twenty-one autoantigens appeared to be related to POAG. Bioinformatic analysis revealed that the platelet-derived growth factor receptor beta (PDGFRB) pathway involved in TM fibrosis was particularly rich in POAG-related antigens. Antibodies to threonine-tRNA ligase (TARS), component 1 Q subcomponent-binding protein (C1QBP) and paraneoplastic antigen Ma2 (PNMA2) showed significantly (P < 0.05) higher levels in POAG patients as validated by protein microarray.

CONCLUSION

This study provides new insights into autoimmunity in health and glaucoma. Bioinformatic analysis of POAG-related autoantigens showed a strong association with the PDGFRB pathway and also increased levels of PNMA2, TARS, and C1QBP autoantibodies in the serum of POAG patients as potential glaucoma biomarkers.

Upregulation of miR‑132‑3p in cholangiocarcinoma tissues: A study based on RT‑qPCR, The Cancer Genome Atlas miRNA sequencing, Gene Expression Omnibus microarray data and bioinformatics analyses

MicroRNAs (miRNAs/miRs) have been reported to be closely associated with numerous human diseases, including cholangiocarcinoma (CCA). However, the number of miRNAs known to be involved in CCA is limited, and the association between miR-132-3p and CCA remains unknown. In the present study, the clinical role of miR-132-3p and its potential signaling pathways were investigated by multiple approaches. Reverse transcription-quantitative PCR (RT-qPCR), CCA-associated Gene Expression Omnibus (GEO), ArrayExpress and Sequence Read Archive (SRA) miRNA-microarray or miRNA-sequencing data were screened, and meta-analyses were conducted, in order to calculate the receiver operating characteristic (ROC) curve and standardized mean difference (SMD). The predicted target genes of miR-132-3p were obtained from 12 online databases and were combined with the downregulated differentially expressed genes identified in the RNA-sequencing data of CCA. Gene Ontology annotation and pathway analysis were performed in WebGestalt. Protein-protein interaction analyses were conducted in STRING. The Cancer Genome Atlas (TCGA) mRNA expression profiles were used to validate the expression levels of hub genes at the mRNA level. The Human Protein Atlas was used to identify the protein expression levels of hub genes in CCA tissues and non-tumor biliary epithelium. The meta-analyses comprised 10 groups of RT-qPCR data, eight GEO microarray datasets and one TCGA miRNA-sequencing dataset. The SMD of miR-132-3p in CCA was 0.75 (95% CI: 0.25, 1.24), which indicated that miR-132-3p was overexpressed in CCA tissues. This finding was supported by a summary ROC value of 0.80 (95% CI: 0.76, 0.83). The pooled sensitivity and specificity were 0.81 (95% CI: 0.59, 0.93) and 0.71 (95% CI: 0.58, 0.81), respectively. The relative expression level of miR-132-3p in the early stage of CCA (stages I–II) was 6.8754±0.5279, which was markedly lower than that in the advanced stage (stages III–IVB), 7.3034±0.3267 (P=0.003). Consistently, the miR-132-3p level in low-grade CCA (grades G1-G2) was 6.7581±0.5297, whereas it was 7.1191±0.4651 in patients with high-grade CCA (grades G3-G4) (P=0.037). Furthermore, 555 potential target genes of miR-132-3p in CCA were mainly enriched in the ‘Focal Adhesion-PI3K-Akt-mTOR-signaling pathway’. In conclusion, upregulation of miR-132-3p may serve a pivotal role in the tumorigenesis and progression of CCA by targeting different pathways. Further in vitro and in vivo studies are required to support the current findings.

Autoantibody Biomarker Discovery in Primary Open Angle Glaucoma Using Serological Proteome Analysis (SERPA)

Glaucoma is an optic neurological disorder and the leading cause of irreversible blindness worldwide, with primary open angle glaucoma (POAG) as its most prevalent form. An early diagnosis of the disease is crucial to prevent loss of vision. Mechanisms behind glaucoma pathogenesis are not completely understood, but disease related alterations in the serological autoantibody profile indicate an immunologic component. These changes in immunoreactivity may serve as potential biomarkers for glaucoma diagnostics. We aimed to identify novel disease related autoantibodies targeting antigens in the trabecular meshwork as biomarkers to support early detection of POAG. We used serological proteome analysis (SERPA) for initial autoantibody profiling in a discovery sample set. The identified autoantibodies were validated by protein microarray analysis in a larger cohort with 60 POAG patients and 45 control subjects. In this study, we discovered CALD1, PGAM1, and VDAC2 as new biomarker candidates. With the use of artificial neural networks, the panel of these candidates and the already known markers HSPD1 and VIM was able to classify subjects into POAG patients and non-glaucomatous controls with a sensitivity of 81% and a specificity of 93%. These results suggest the benefit of these potential autoantibody biomarkers for utilization in glaucoma diagnostics.

Classical Immunoproteomics: Serological Proteome Analysis (SERPA) for Antigen Identification

The study of the humoral immune response to infectious and chronic diseases is important for understanding the disease progression, identification of protective antigens, vaccine development, and discovery of biomarkers for early diagnosis. Proteomic approaches, including serological proteome analysis (SERPA), have been used to identify the repertoire of immunoreactive proteins in various diseases. In this chapter, we provide an outline of the SERPA approach, using the analysis of sera from mice vaccinated with a live attenuated tularemia vaccine as an example.

Translational Bioinformatics for Cholangiocarcinoma: Opportunities and Challenges

Translational bioinformatics is becoming a driven force and a new scientific paradigm for cancer research in the era of big data. To promote the cross-disciplinary communication and research, we take cholangiocarcinoma as an example to review the present status and the future perspectives of the bioinformatics models applied in cancer study. We first summarize the present application of computational methods to the study of cholangiocarcinoma ranged from pattern recognition of biological data, knowledge based data annotation to systems biological level modeling and clinical translation. Then the future opportunities and challenges about database or knowledge base building, novel model developing and molecular mechanism exploring as well as the intelligent decision supporting system construction for the precision diagnosis, prognosis and treatment of cholangiocarcinoma are discussed.

Antigenicity of Bovine Pericardium Determined by a Novel Immunoproteomic Approach

Despite bovine pericardium (BP) being the primary biomaterial used in heart valve bioprostheses, recipient graft-specific immune responses remain a significant cause of graft failure. Consequently, tissue antigenicity remains the principal barrier for expanding use of such biomaterials in clinical practice. We hypothesize that our understanding of BP antigenicity can be improved by application of a combined affinity chromatography shotgun immunoproteomic approach to identify antigens that have previously been overlooked. Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS) analysis of affinity chromatography purified antigens resulted in identification of 133 antigens. Most importantly, antigens were identified from all subcellular locations, including 18 integral membrane protein antigens. Critically, isoforms of several protein families were found to be antigenic suggesting the possibility that shared epitope domains may exist. Furthermore, proteins associated with immune, coagulation, and inflammatory pathways were over-represented, suggesting that these biological processes play a key role in antigenicity. This study brings to light important determinants of antigenicity in a clinically relevant xenogeneic biomaterial (i.e. BP) and further validates a rapid, high-throughput method for immunoproteomic antigen identification.

Detection of Autoantibodies to Vascular Endothelial Growth Factor Receptor-3 in Bile Duct Ligated Rats and Correlations with a Panel of Traditional Markers of Liver Diseases

There is a need for new noninvasive biomarkers (NIBMs) able to assess cholestasis and fibrosis in chronic cholestatic liver diseases (CCLDs). Tumorigenesis can arise from CCLDs. Therefore, autoantibodies to tumor-associated antigens (TAA) may be early produced in response to abnormal self-antigen expression caused by cholestatic injury. Vascular endothelial growth factor receptor-3 (VEGFR-3) has TAA potential since it is involved in cholangiocytes and lymphatic vessels proliferations during CCLDs. This study aims to detect autoantibodies directed at VEGFR-3 during bile duct ligation- (BDL-) induced cholestatic injury in rat sera and investigate whether they could be associated with traditional markers of liver damage, cholestasis, and fibrosis. An ELISA was performed to detect anti-VEGFR-3 autoantibodies in sera of rats with different degree of liver injury and results were correlated with aminotransferases, total bilirubin, and the relative fibrotic area. Mean absorbances of anti-VEGFR-3 autoantibodies were significantly increased from week one to week five after BDL. The highest correlation was observed with total bilirubin (R (2) = 0.8450, P = 3.04e - 12). In conclusion, anti-VEGFR-3 autoantibodies are early produced during BDL-induced cholestatic injury, and they are closely related to cholestasis, suggesting the potential of anti-VEGFR-3 autoantibodies as NIBMs of cholestasis in CCLDs and justifying the need for further investigations in patients with CCLD.