Serum anti-MDM2 and anti-c-Myc autoantibodies as biomarkers in the early detection of lung cancer

Mechanism of luteolin against non-small-cell lung cancer: a study based on network pharmacology, molecular docking, molecular dynamics simulation, and in vitro experiments

Introduction

Luteolin, a naturally occurring flavonoid compound, demonstrates promising anti-cancer properties. However, its mechanism against non-small-cell lung cancer (NSCLC) remains unknown. This study employed network pharmacology, molecular docking, molecular dynamics simulation (MDS), and in vitro experiments to investigate the potential mechanisms by which luteolin against NSCLC.

Methods

Initially, the potential targets of luteolin and NSCLC-related targets were identified from public databases such as TCMSP, GeneCards, OMIM, DrugBank, and TTD. Subsequently, the protein-protein interaction (PPI) network screening and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted. The binding affinity and stability of luteolin with the core targets were assessed using molecular docking and MDS. Finally, the results were validated by in vitro experiments.

Results

A total of 56 luteolin targets and 2145 NSCLC-related targets were identified. Six core targets, TP53, EGFR, AKT1, TNF, JUN, and CASP3, were screened via the PPI network. The GO and KEGG analyses indicated that luteolin's activity against NSCLC potentially involves PI3K-Akt, NF-kappa B, and other signaling pathways. Molecular docking revealed that luteolin had high binding affinity with the core targets. MDS confirmed the stable interaction between luteolin and key proteins TP53 and AKT1. in vitro, luteolin significantly inhibited the proliferation and migration of A549 cells, while also inducing apoptosis. In addition, luteolin downregulated the expression of p-Akt (Ser473), MDM2, and Bcl-2 but upregulated the expression of p53 and Bax, which was consistent with the effect of LY294002.

Conclusion

Luteolin had a good anti-NSCLC effect, and the apoptosis-inducing effect might be related to the Akt/MDM2/p53 signaling pathway.

Association of elevated autoantibody to high expression of GNAS in hepatocellular carcinoma

Purpose

This study was based on hepatocellular carcinoma (HCC) patients of early-stage to explore the diagnostic capability and possible production causes of anti-GNAS autoantibody.

Methods

We evaluated the frequency of anti-GNAS autoantibody in sera from patients with early-stage HCC by enzyme-linked immunosorbent assay (ELISA) and the expression of GNAS protein in early-stage HCC tissues by immunohistochemistry. Western blotting (WB) and real-time polymerase chain reaction (RT-PCR) were utilized to examine the expressions of GNAS protein and mRNA in cell lines. GEO and International Cancer Genome Consortium (ICGC) databases were inquired to explore mRNA expression and mutation of GNAS in HCC tissues.

Results

The positive rates of anti-GNAS autoantibody in HCC patients at clinical stage I (78.1 %) and clinical stage II (57.1 %) were all significantly higher than that in healthy control (20 %). There was also a significant difference in GNAS protein expression between HCC and its adjacent normal liver tissues. The results from WB and RT-PCR showed a significant difference at the mRNA level but no statistical difference at the protein level between HCC and normal liver cell lines. The difference in mRNA level between HCC and adjacent normal liver tissues was verified to be significant. Furthermore, the ICGC database demonstrated a 10.6 % mutation frequency for GNAS in HCC patients.

Conclusion

The coordination of elevated anti-GNAS autoantibody, high expression of GNAS in the mRNA and protein levels in HCC, and high frequency of GNAS mutation indicates that anti-GNAS autoantibody may be used as an early indicator of HCC.

The Importance of the Immune System and Molecular Cell Signaling Pathways in the Pathogenesis and Progression of Lung Cancer

Lung cancer is a disease that in recent years has become one of the greatest threats to modern society. Every year there are more and more new cases and the percentage of deaths caused by this type of cancer increases. Despite many studies, scientists are still looking for answers regarding the mechanisms of lung cancer development and progression, with particular emphasis on the role of the immune system. The aim of this literature review was to present the importance of disorders of the immune system and the accompanying changes at the level of cell signaling in the pathogenesis of lung cancer. The collected results showed that in the process of immunopathogenesis of almost all subtypes of lung cancer, changes in the tumor microenvironment, deregulation of immune checkpoints and abnormalities in cell signaling pathways are involved, which contribute to the multistage and multifaceted carcinogenesis of this type of cancer. We, therefore, suggest that in future studies, researchers should focus on a detailed analysis of tumor microenvironmental immune checkpoints, and to validate their validity, perform genetic polymorphism analyses in a wide range of patients and healthy individuals to determine the genetic susceptibility to lung cancer development. In addition, further research related to the analysis of the tumor microenvironment; immune system disorders, with a particular emphasis on immunological checkpoints and genetic differences may contribute to the development of new personalized therapies that improve the prognosis of patients.

Blood protein biomarkers in lung cancer

Lung cancer has consistently ranked first as the cause of cancer-associated mortality. The 5-year survival rate has risen slowly, and the main obstacle to improving the prognosis of patients has been that lung cancer is usually diagnosed at an advanced or incurable stage. Thus, early detection and timely intervention are the most effective ways to reduce lung cancer mortality. Tumor-specific molecules and cellular elements are abundant in circulation, providing real-time information in a noninvasive and cost-effective manner during lung cancer development. These circulating biomarkers are emerging as promising tools for early detection of lung cancer and can be used to supplement computed tomography screening, as well as for prognosis prediction and treatment response monitoring. Serum and plasma are the main sources of circulating biomarkers, and protein biomarkers have been most extensively studied. In this review, we summarize the research progress on three most common types of blood protein biomarkers (tumor-associated antigens, autoantibodies, and exosomal proteins) in lung cancer. This review will potentially guide researchers toward a more comprehensive understanding of candidate lung cancer protein biomarkers in the blood to facilitate their translation to the clinic.

CircRNA6783 Inhibits Cell Proliferation and Promotes Apoptosis in Lung Adenocarcinoma

Purpose

Circular RNA (circRNA) serves an important role in tumour genesis and development. But, little is known about its role in lung adenocarcinoma (LA). This study aimed to investigate circRNA6783 expression in peripheral whole blood (PWB) of LA and controls and explore its effect on proliferation and apoptosis in human lung adenocarcinoma cells (LAC).

Patients and Methods

The levels of circRNA6783 in LA cell lines and peripheral whole blood (PWB) of 40 patients and 30 controls were detected by real-time quantitative reverse transcription-polymerase chain reaction (RT-PCR). In order to explore the effect of circRNA6783 on LA behavior, we overexpressed circRNA6783 in NCI-H1975 cells. The impact on the proliferation of tumor cells was then examined by Cell Counting Kit 8 (CCK8) assay, and the effects on apoptosis in the cell line were detected using flow cytometry.

Results

The expression levels of circRNA6783 were significantly higher in LA cell lines and PWB (P < 0.05). The diagnostic value of the area under the receiver operating characteristic curve (AUC) was 0.830, with a sensitivity of 60% and specificity of 96.7%. In addition, functional experiments showed that overexpression of circRNA6783 restrained cell proliferation, significantly increased spontaneous apoptosis.

Conclusion

CircRNA6783 was upregulated in LA PWB. In vitro assessment demonstrated that circRNA6783 could act as a potential biomarker for LA diagnosis.

Serum Autoantibodies against LRDD, STC1, and FOXA1 as Biomarkers in the Detection of Ovarian Cancer

Purpose

This study is aimed at evaluating serum autoantibodies against four tumor-associated antigens, including LRDD, STC1, FOXA1, and EDNRB, as biomarkers in the immunodiagnosis of ovarian cancer (OC).

Methods

The autoantibodies against LRDD, STC1, FOXA1, and EDNRB were measured using an enzyme-linked immunosorbent assay (ELISA) in 94 OC patients and 94 normal healthy controls (NHC) in the research group. In addition, the diagnostic values of different autoantibodies were validated in another independent validation group, which comprised 136 OC patients, 136 NHC, and 181 patients with benign ovarian diseases (BOD).

Results

In the research group, autoantibodies against LRDD, STC1, and FOXA1 had higher serum titer in OC patients than NHC (P < 0.001). The area under receiver operating characteristic curves (AUCs) of these three autoantibodies were 0.910, 0.879, and 0.817, respectively. In the validation group, they showed AUCs of 0.759, 0.762, and 0.817 and sensitivities of 49.3%, 42.7%, and 48.5%, respectively, at specificity over 90% for discriminating OC patients from NHC. For discriminating OC patients from BOD, they showed AUCs of 0.718, 0.729, and 0.814 and sensitivities of 47.1%, 39.0%, and 51.5%, respectively, at specificity over 90%. The parallel analyses demonstrated that the combination of anti-LRDD and anti-FOXA1 autoantibodies achieved the optimal diagnostic performance with the sensitivity of 58.1% at 87.5% specificity and accuracy of 72.8%. The positive rate of the optimal autoantibody panel improved from 62.4% to 87.1% when combined with CA125 in detecting OC patients.

Conclusion

Serum autoantibodies against LRDD, STC1, and FOXA1 have potential diagnostic values in detecting OC.

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

Immunoglobulin M (IgM) autoantibodies, as the early appearing antibodies in humoral immunity when stimulated by antigens, might be excellent biomarkers for the early detection of lung cancer (LC). We aimed to develop a multi-analyte integrative model combining IgM autoantibodies and a traditional tumor biomarker that could be a valuable and powerful auxiliary diagnostic tool and might improve the accuracy of early detection of lung adenocarcinoma (LUAD). A customized protein array based on cancer driver genes was constructed and applied in the discovery cohort consisting of 68 LUAD patients and 68 normal controls (NCs); 31 differentially expressed IgM autoantibodies were identified. The top 5 candidate IgM autoantibodies [based on the area under the receiver operating characteristic curve (AUC) ranking], namely, TSHR, ERBB2, survivin, PIK3CA, and JAK2, were validated in the validation cohort using enzyme-linked immunosorbent assay (ELISA), which included 147 LUAD samples, 72 lung squamous cell carcinoma (LUSC) samples, 44 small cell lung carcinoma (SCLC) samples, and 147 NCs. These indicators presented diagnostic capacity for LUAD, with AUCs of 0.599, 0.613, 0.579, 0.601, and 0.633, respectively (p < 0.05). However, none of them showed a significant difference between the SCLC and NC groups, and only the IgM autoantibody against JAK2 showed a higher expression in LUSC than in NC (p = 0.046). Through logistic regression analysis, with the five IgM autoantibodies and carcinoembryonic antigen (CEA), one diagnostic model was constructed for LUAD. The model yielded an AUC of 0.827 (sensitivity = 56.63%, specificity = 93.98%). The diagnostic efficiency was superior to that of either CEA (AUC = 0.692) or IgM autoantibodies alone (AUC = 0.698). Notably, the accuracy of this model in early-stage LUAD reached 83.02%. In conclusion, we discovered and identified five novel IgM indicators and developed a multi-analyte model combining IgM autoantibodies and CEA, which could be a valuable and powerful auxiliary diagnostic tool and might improve the accuracy of early detection of LUAD.

Seven tumor-associated autoantibodies as a serum biomarker for primary screening of early-stage non-small cell lung cancer

Objective

The purpose of this study was to analyze the levels of tumor‐associated autoantibodies (TAAbs) in lung diseases and determine their diagnostic efficiency in early‐stage non‐small cell lung cancer (NSCLC).

Methods

We retrospectively analyzed the levels of 7‐TAAbs in 177 newly diagnosed early‐stage NSCLC patients, 202 patients with lung benign diseases and 137 healthy cases. The levels of a panel of 7‐TAAbs, including p53, GAGE7, PGP9.5, CAGE, MAGE A1, SOX2, GBU4‐5, were measured by ELISA.

Results

The serum levels of p53, GAGE7, PGP9.5, CAGE, MAGE A1, SOX2, and GBU4‐5 were not statistically different among NSCLC, benign and healthy groups (p > 0.05). The area under the curve (AUC) of 7‐TAAbs was all lower than 0.70. The sensitivity of combined detection was the highest (23.73%), while the specificity was the lowest (88.79%). The positive rates of PGP9.5, SOX2, and combined detection were significantly different among the three groups (p < 0.05). Among them, PGP9.5 and combined detection were significantly different between the NSCLC and benign groups (p < 0.05), PGP9.5, SOX2 and combined detection were significantly different between the NSCLC and healthy groups (p < 0.05).

Conclusions

The diagnostic efficiency of 7‐TAAbs in early‐stage NSCLC was not high, so it cannot be used alone as a screening method for NSCLC.

Serum Anti-PDLIM1 Autoantibody as Diagnostic Marker in Ovarian Cancer

Background

Serum autoantibodies (AAbs) against tumor-associated antigens (TAAs) could be useful biomarkers for cancer detection. This study aims to evaluate the diagnostic value of autoantibody against PDLIM1 for improving the detection of ovarian cancer (OC).

Methods

Immunohistochemistry (IHC) test in tissue array containing 280 OC tissues, 20 adjacent tissues, and 8 normal ovarian tissues was performed to analyze the expression of PDLIM1 in tissues. Enzyme-linked immunosorbent assay (ELISA) was employed to measure the autoantibody to PDLIM1 in 545 sera samples from 182 patients with OC, 181 patients with ovarian benign diseases, and 182 healthy controls.

Results

The results of IHC indicated that 84.3% (236/280) OC tissues were positively stained with PDLIM1, while no positive staining was found in adjacent or normal ovarian tissues. The frequency of anti-PDLIM1 autoantibody was significantly higher in OC patients than that in healthy and ovarian benign controls in both training (n=122) and validation (n=423) sets. The area under the curves (AUCs) of anti-PDLIM1 autoantibody for discriminating OC from healthy controls were 0.765 in training set and 0.740 in validation set, and the AUC of anti-PDLIM1 autoantibody for discriminating OC from ovarian benign controls was 0.757 in validation set. Overall, it was able to distinguish 35.7% of OC, 40.6% of patients with early-stage, and 39.5% of patients with late-stage. When combined with CA125, the AUC increased to 0.846, and 79.2% of OC were detected, which is statistically higher than CA125 (61.7%) or anti-PDLIM1(35.7%) alone (p<0.001). Also, anti-PDLIM1 autoantibody could identify 15% (18/120) of patients that were negative with CA125 (CA125 <35 U/ml).

Conclusions

The anti-PDLIM1 autoantibody response in OC patients was positively correlated with PDLIM1 high expression in OC tissues, suggesting that the autoantibody against PDLIM1 might have the potential to be a novel serological biomarker of OC, serving as a complementary measure of CA125, which could improve the power of OC detection.

UBE2V2 Positively Correlates With PD-L1 Expression and Confers Poor Patient Survival in Lung Adenocarcinoma

This research aims to explore the diagnostic and prognostic value of ubiquitin-conjugating enzyme E2 variant 2 (UBE2V2) in lung adenocarcinoma (LUAD). The expression of UBE2V2 in clinical specimens was evaluated by bioinformatics analyses and immunohistochemistry. Bioinformatics analyses relying on the The Cancer Genome Atlas (TCGA) database suggested the elevated UBE2V2 mRNA levels in LUAD in comparison to adjacent normal tissues. Gene set enrichment analyses and gene ontology term enrichment analyses further showed the involvement of UBE2V2 in the modulation of cell cycle and immune associated signaling. The correlation analyses in TCGA LUAD data set revealed the positive correlation between UBE2V2 and CCNE1, CCNE2, CCNA2, CCNB1, CCNB2, cyclin-dependent kinase (CDK)2, CDK4, and CDK1 at the mRNA level. Moreover, UBE2V2 mRNA levels were positively correlated with PD-L1 mRNA levels, the T classification, and poor survival of LUAD patients, and were negatively correlated with type II interferon response. Consistent with the results obtained from TCGA data mining, immunohistochemistry demonstrated that UBE2V2 protein levels were upregulated in LUAD in comparison to normal tissues and were positively associated with T classification. Intriguingly, a positive correlation between UBE2V2 protein levels and PD-L1 expression was also elucidated in clinical samples. Besides, UBE2V2 expression indicated a poor prognosis in LUAD patients. Our study found that UBE2V2 was identified as an independent prognostic indicator for LUAD and might serve as an alternative target for LUAD treatment.

Autoimmune Responses in Oncology: Causes and Significance

Specific anti-tumor immune responses have proven to be pivotal in shaping tumorigenesis and tumor progression in solid cancers. These responses can also be of an autoimmune nature, and autoantibodies can sometimes be present even before the onset of clinically overt disease. Autoantibodies can be generated due to mutated gene products, aberrant expression and post-transcriptional modification of proteins, a pro-immunogenic milieu, anti-cancer treatments, cross-reactivity of tumor-specific lymphocytes, epitope spreading, and microbiota-related and genetic factors. Understanding these responses has implications for both basic and clinical immunology. Autoantibodies in solid cancers can be used for early detection of cancer as well as for biomarkers of prognosis and treatment response. High-throughput techniques such as protein microarrays make parallel detection of multiple autoantibodies for increased specificity and sensitivity feasible, affordable, and quick. Cancer immunotherapy has revolutionized cancer treatments and has made a considerable impact on reducing cancer-associated morbidity and mortality. However, immunotherapeutic interventions such as immune checkpoint inhibition can induce immune-related toxicities, which can even be life-threatening. Uncovering the reasons for treatment-induced autoimmunity can lead to fine-tuning of cancer immunotherapy approaches to evade toxic events while inducing an effective anti-tumor immune response.

Autoantibodies to tumor-associated antigens in lung cancer diagnosis

Lung cancer (LC) accounts for the majority of cancer-related deaths worldwide. Although screening the high-risk population by low-dose CT (LDCT) has reduced mortality, the cost and high false positivity rate has prevented its general diagnostic use. As such, better and more specific minimally invasive biomarkers are needed in general and for early LC detection, specifically. Autoantibodies produced by humoral immune response to tumor-associated antigens (TAA) are emerging as a promising noninvasive biomarker for LC. Given the low sensitivity of any one single autoantibody, a panel approach could provide a more robust and promising strategy to detect early stage LC. In this review, we summarize the background of TAA autoantibodies (TAAb) and the techniques currently used for identifying TAA, as well as recent findings of LC specific antigens and TAAb. This review provides guidance toward the development of accurate and reliable TAAb as immunodiagnostic biomarkers in the early detection of LC.

Clinical value of seven autoantibodies combined detection in the diagnosis of lung cancer

Background

To analyze the clinical value of seven autoantibodies (p53, PGP9.5, SOX2, GAGE7, GBU4‐5, MAGE A1 and CAGE) in lung cancer patients.

Methods

ELISA was used to determine serum levels of seven autoantibodies in 177 patients with lung cancer, 201 healthy persons, and 210 patients with benign pulmonary diseases. Positive rates of 7 autoantibodies were analyzed; receiver operating characteristic (ROC) curves were drawn to analyze their diagnostic efficiency in lung cancer and to compare the positive rate of seven kinds of autoantibody combined detection of lung cancer patients with different clinicopathological features.

Results

The positive rate of seven autoantibodies in all subjects was 13.44%. The positive rate of seven autoantibodies in lung cancer was 25.42%. The positive rate of the combined detection of seven autoantibodies in the lung cancer group was significantly higher than that in healthy control group (χ² = 19.76, P < .001) and benign lung disease group (χ² = 21.44, P < .001). Sensitivity, specificity, and AUC^ROC of the seven autoantibodies were 25.42%, 91.75%, and 0.683, respectively. Sensitivity and AUC^ROC were higher than those of the single autoantibody detection. Positive rates of seven autoantibodies in different pathological types and clinical stages of lung cancer patients were significantly different (P < .05).

Conclusions

The combined detection of 7 autoantibodies in lung cancer has some clinical value for the auxiliary diagnosis of lung cancer.

Establishment and validation of an immunodiagnostic model for prediction of breast cancer

Serum autoantibodies that react with tumor-associated antigens (TAAs) can be used as potential biomarkers for diagnosis of cancer. This study aims to evaluate the immunodiagnostic value of 11 anti-TAAs autoantibodies for detection of breast cancer (BC) and establish a diagnostic model for distinguishing BC from normal human controls (NHC) and benign breast diseases (BBD). Sera from 10 BC patients and 10 NHC were used to detect 11 anti-TAAs autoantibodies by western blotting. The 11 anti-TAAs autoantibodies were further assessed in 983 sera by relative quantitative enzyme-linked immunosorbent assay (ELISA). Binary logistic regression and Fisher linear discriminant analysis were conducted to establish a prediction model by using 184 BC and 184 NHC (training cohort, n = 568) and validated by leave-one-out cross-validation. Logistic regression model was selected to establish the prediction model. Results were validated using an independent validation cohort (n = 415). The five anti-TAAs (p53, cyclinB1, p16, p62, 14-3-3ξ) autoantibodies were selected to construct the model with the area under the curve (AUC) of 0.943 (95% CI, 0.919–0.967) in training cohort and 0.916 (95% CI, 0.886–0.947) in the validation cohort. In the identification of BC and BBD, AUCs were 0.881 (95% CI, 0.848–0.914) and 0.849 (95% CI, 0.803–0.894) in training and validation cohort, respectively. In summary, our study indicates that the immunodiagnostic model can distinguish BC from NHC and BC from BBD and this model may have a potential application in immunodiagnosis of breast cancer.

A panel of autoantibodies against tumor-associated antigens in the early immunodiagnosis of lung cancer

OBJECTIVE

Lung cancer (LC) is one of the most common malignant tumors worldwide with low five-year survival rate due to lack of effective diagnosis. This study aims to find an optimal combination of autoantibodies for detecting of early-stage LC.

METHODS

Nine relatively novel autoantibodies against tumor-associated (TAAs) (PSIP1, TOP2A, ACTR3, RPS6KA5, HMGB3, MMP12, GREM1, ZWINT and NUSAP1) were detected by using ELISA. Diagnostic models were developed by using the training set (n = 644) and further validated in another independent set (n = 248). We also evaluated the diagnostic accuracy of the model to detect benign lung diseases (BLD) from the early-stage lung cancer.

RESULTS

The areas under the receiver operating characteristic curve (AUC) for the model with three TAAs panel (GREM1, HMGB3 and PSIP1) was 0.711(95% CI 0.674-0.746) in the training set and 0.858 (95% CI 0.808-0.899) in the validation set, which demonstrated a higher diagnostic capability. The AUC of this three TAAs model was 0.833 (95%CI 0.780-0.878) in discriminating LC from BLD. This model could identify early-stage LC patients from normal control (NC) individuals, with AUC of 0.687(95% CI 0.634-0.736) in training set and AUC of 0.920(95% CI 0.860-0.960) in validation set, and the overall AUC for early-stage LC was 0.779(95% CI 0.739-0.816) when the training set and validation set were combined.

CONCLUSIONS

The model with three TAAs panel would detect LC with higher effectiveness, and might be potential screening method for the early LC.

Autoantibodies as diagnostic biomarkers for lung cancer: A systematic review

Lung cancer (LC) accounts for the largest number of tumor-related deaths worldwide. As the overall 5-year survival rate of LC is associated with its stages at detection, development of a cost-effective and noninvasive cancer screening method is necessary. We conducted a systematic review to evaluate the diagnostic values of single and panel tumor-associated autoantibodies (TAAbs) in patients with LC. This review included 52 articles with 64 single TAAbs and 19 with 20 panels of TAAbs. Enzyme-linked immunosorbent assays (ELISA) were the most common detection method. The sensitivities of single TAAbs for all stages of LC ranged from 3.1% to 92.9% (mean: 45.2%, median: 37.1%), specificities from 60.6% to 100% (mean: 88.1%, median: 94.9%), and AUCs from 0.416 to 0.990 (mean: 0.764, median: 0.785). The single TAAb with the most significant diagnostic value was the autoantibody against human epididymis secretory protein (HE4) with the maximum sensitivity 91% for NSCLC. The sensitivities of the panel of TAAbs ranged from 30% to 94.8% (mean: 76.7%, median: 82%), specificities from 73% to 100% (mean: 86.8%, median: 89.0%), and AUCs from 0.630 to 0.982 (mean: 0.821, median: 0.820), and the most significant AUC value in a panel (M13 Phage 908, 3148, 1011, 3052, 1000) was 0.982. The single TAAb with the most significant diagnostic calue for early stage LC, was the autoantibody against Wilms tumor protein 1 (WT1) with the maximum sensitivity of 90.3% for NSCLC and its sensitivity and specificity in a panel (T7 Phage 72, 91, 96, 252, 286, 290) were both above 90.0%. Single or TAAbs panels may be useful biomarkers for detecting LC patients at all stages or an early-stage in high-risk populations or health people, but the TAAbs panels showed higher detection performance than single TAAbs. The diagnostic value of the panel of six TAAbs, which is higher than the panel of seven TAAbs, may be used as potential biomarkers for the early detection of LC and can probably be used in combination with low-dose CT in the clinic.

Five tumor-associated autoantibodies expression levels in serum predict lung cancer and associate with poor outcome

Background

This study aims to evaluate diagnostic feasibility of the tumor-associated autoantibodies and their clinical significance in lung cancer.

Methods

Blood samples were collected from 352 lung cancer patients and 226 healthy individuals. Immunohistochemical staining was used to evaluate the expression of autoantibodies in 69 cases of lung cancer tissues. Enzyme-linked immunosorbent assay (ELISA) was performed to measure the five autoantibodies levels in serum from lung cancer patients and healthy controls.

Results

Higher expression of GAGE7, MAGEA1, PGP9.5, CAGE and p53 were found in lung cancer tissues than normal tissues from the cancer genome atlas (TCGA) database. The expression levels of the five tumor-associated autoantibodies in lung cancer tissues were positively associated with those statuses in serum. There were significantly higher levels of each autoantibody in lung cancer patients than healthy individuals. The area under curve (AUC) for GAGE7, MAGEA1, PGP9.5, CAGE and p53 in diagnosis of lung cancer were 0.787, 0.641, 0.873, 0.825 and 0.749, respectively. With combination of these five autoantibodies by the logistic regression model, 0.891 of AUC was shown. In addition, the level of each autoantibody was increased in the advanced stage. Particularly, the level of PGP9.5 was significantly higher in the advanced T stage, N stage and TNM stage and CAGE was significantly elevated in the advanced N stage.

Conclusions

Summarily, autoantibodies levels of GAGE7, MAGEA1, PGP9.5, CAGE and p53 in serum could be used for the diagnosis of lung cancer and PGP9.5 may predict poor prognosis for the patients with lung cancer.

Renal Epithelioid Angiomyolipoma Undergoing Aggressive Clinical Outcome: The MDM2 Expression in Tumor Cells of Two Cases

Epithelioid angiomyolipoma (EAML) has been known as a potentially malignant tumor which occasionally recur and/or metastasize to other organs, and clinically and pathologically recognized as distinct entity. However, the mechanisms of recurrence and/or metastasis (recurrence/metastasis) has still remained unknown. Here, we report two cases of renal EAML associated with recurrence/metastasis, and three cases of EAML in kidney or liver without recurrence/metastasis. According to the previous histological predictive models of EAML, the primary tumor was classified as low risk group in one of the cases with recurrence/metastasis in spite of its malignant behavior. Therefore, we considered that further investigation about the mechanisms of recurrence/metastasis in EAML is required for a malignancy prediction. We focused on some cell-cycle modulators, including mouse double minute 2 homolog (MDM2), which is ubiquitin ligase well-known to promote malignant behaviors by p53 ubiquitination and degradation, and also other cellular processes including genomic instability and epithelial-mesenchymal transition in p53-independent manners in various human malignancies. Immunohistochemical evaluation revealed that MDM2 protein expression increased stepwise throughout every steps of metastasis/recurrence in both cases, although it was negative in primary tumors. In conclusion, this is the first study demonstrating that MDM2 could play an important role in the molecular mechanisms of recurrence/metastasis of EAML. Further analyses focusing on MDM2 pathway could contribute to the identification of novel prognostic factors and/or therapeutic targets in EAML patients.

Multiplexed Autoantibody Signature for Serological Detection of Canine Mammary Tumours

Spontaneously occurring canine mammary tumours (CMTs) are the most common neoplasms of female unspayed dogs and are of potential importance as models for human breast cancer as well. Mortality rates are thrice higher in dogs as compared to humans with breast cancer, which can partly be attributed to lack of diagnostic techniques for their early detection. Human breast cancer studies reveal role of autoantibodies in early cancer diagnosis and also the usefulness of autoantibody panels in increasing the sensitivity, as well as, specificity of diagnostic assays. Therefore, in this study, we took advantage of high-throughput Luminex technique for developing a multiplex assay to detect autoantibody signatures against 5 canine mammary tumour-associated autoantigens (TAAs). These TAAs were expressed separately as fusion proteins with halo tag at the N-terminus, which allows easy and specific covalent coupling with magnetic microspheres. The multiplex assay, comprising a panel of candidate autoantigens (TPI, PGAM1, MNSOD, CMYC & MUC1) was used for screening circulating autoantibodies in 125 dog sera samples, including 75 mammary tumour sera and 50 healthy dog sera. The area under curve (AUC) of the combined panel of biomarkers is 0.931 (p < 0.0001), which validates the discriminative potential of the panel in differentiating tumour patients from healthy controls. The assay could be conducted in 3hrs using only 1ul of serum sample and could detect clinical cases of canine mammary tumour with sensitivity and specificity of 78.6% and 90%, respectively. In this study, we report for the first time a multiplexed assay for detection of autoantibodies in canine tumours, utilizing luminex technology and halo-tag coupling strategy. Further to the best of our knowledge, autoantibodies to CMYC and MUC1 have been reported for the first time in canines in this study.

Blood based biomarkers beyond genomics for lung cancer screening

While there is considerable interest at the present time in the development of so-called liquid biopsy approaches for cancer detection based notably on circulating tumor DNA, there are other types of potential biomarkers that show promise for lung cancer screening and early detection. Here we review approaches and some of the promising markers based on proteomics, metabolomics and the immune response to tumor antigens in the form of autoantibodies.

Sensitive and simultaneous surface plasmon resonance detection of free and p53-bound MDM2 proteins from human sarcomas

Murine double minute 2 (MDM2) is an oncoprotein mediating the degradation of the tumor suppressor p53 protein. The physiological levels of MDM2 protein are closely related to malignant transformation and tumor growth. In this work, the simultaneous and label-free determination of free and p53-bound MDM2 proteins from sarcoma tissue extracts was conducted using a dual-channel surface plasmon resonance (SPR) instrument. Free MDM2 protein was measured in one fluidic channel covered with the consensus double-stranded (ds)-DNA/p53 conjugate, while MDM2 bound to p53 was captured by the consensus ds-DNA immobilized onto the other channel. To achieve higher sensitivity and to confirm specificity, an MDM2-specific monoclonal antibody (2A10) was used to recognize both the free and p53-bound MDM2 proteins. The resultant method afforded a detection limit of 0.55 pM of MDM2. The amenability of the method to the analysis of free and p53-bound MDM2 proteins was demonstrated for normal and sarcoma tissue extracts from three patients. Our data reveal that both free and total MDM2 (free and bound forms combined) proteins from sarcoma tissue extracts are of much higher concentrations than those from normal tissue extracts and the p53-bound MDM2 protein only constitutes a small fraction of the total MDM2 concentration. In comparison with enzyme-linked immunosorbent assay (ELISA), the proposed method possesses higher sensitivity, is more cost-effective, and is capable of determining free and p53-bound MDM2 proteins in clinical samples.

The roles and applications of autoantibodies in progression, diagnosis, treatment and prognosis of human malignant tumours

The existence of autoantibodies towards an individual's own proteins or nucleic acids has been established for more than 100years, and for a long period, these autoantibodies have been believed to be closely associated with autoimmune diseases. However, in recent years, researchers have become more interested in the role and application of autoantibodies in progression, diagnosis, treatment and prognosis of human malignant tumours. Over the past few decades, numerous epidemiological studies have shown that the risk of certain cancers is significantly altered (increased or decreased) in patients with autoimmune diseases, which suggests that autoantibodies may play either promoting or suppressing roles in cancer progression. The idea that autoantibodies are directly involved in tumour progression gains special support by the findings that some antibodies secreted by a variety of cancer cells can promote their proliferation and metastasis. Because the cancer cells generate cell antigenic changes (neoantigens), which trigger the immune system to produce autoantibodies, serum autoantibodies against tumour-associated antigens have been established as a novel type of cancer biomarkers and have been extensively studied in different types of cancer. The autoantibodies as biomarkers in cancer diagnosis are not only more sensitive and specific than antigens, but also could appear before clinical evidences of the tumours, thus disclosing them. The observations that cancer risk is lower in patients with some autoimmune diseases suggest that certain autoantibodies may be protective from certain cancers. Moreover, the presence of autoantibodies in healthy individuals implies that it could be safe to employ autoantibodies to treat cancer. Of note, an autoantibodies derived from lupus murine model received much attention due to their selective cytotoxicity for malignant tumour cell without harming normal ones. These studies showed the therapeutic value of autoantibodies in cancer. In this review, we revisited the pathological or protective role of autoantibodies in cancer progression, summarize the application of autoantibodies in cancer diagnosis and prognosis, and discuss the value of autoantibodies in cancer therapy. The studies established to date suggest that autoantibodies not only regulate cancer progression but also promise to be valuable instruments in oncological diagnosis and therapy.

Combined detection of dickkopf-1 subtype classification autoantibodies as biomarkers for the diagnosis and prognosis of non-small cell lung cancer

Purpose

This study aims to identify the clinical significance of serum autoantibodies against dickkopf-1 (DKK1) and evaluate their feasibility in the immunodiagnosis and prognosis of non-small cell lung cancer (NSCLC).

Experimental design

Epitope mapping by peptide microarray-based serum screening of NSCLC patients (n=72) and healthy controls (n=16) was performed. Indirect ELISA with peptides was used to measure the serum levels of autoantibodies in 206 NSCLC patients and 99 healthy controls. A 3-year follow-up was monitored to evaluate the correlation between serological levels of autoantibodies and overall survival (OS) and progression-free survival (PFS).

Results

Four highly reactive epitopes were identified, which included peptides 67–84 (Pep A), 37–54 (Pep B), 145–156 (Pep C) and 247–261 (Pep D). The autoantibodies levels were considerably higher in sera of NSCLC patients compared with controls (P<0.001), and a highly significant correlation with distant metastases was observed (Pep A: P=0.09, Pep B: P<0.01, Pep C: P<0.01 and Pep D: P<0.01). High levels of antibody subtype to Pep B were remarkably associated with better OS (P=0.004) and PFS (P=0.006). Subsequent Cox regression analysis disclosed that antibody to Pep B was an independent prognostic factor for NSCLC (OS: P=0.008, HR =0.435, 95% CI 0.236–0.802; PFS: P=0.032, HR =0.533, 95% CI 0.322–0.950).

Conclusion

Identified linear epitopes of antigens by peptide microarray are easily available, and subtype classification of DKK1 autoantibodies as novel biomarkers for the diagnosis and prognosis of NSCLC. Our results also highlight the antibody subtype to Pep B as the most valuable biomarker for favorable prognosis of NSCLC.

Serum autoantibodies against a panel of 15 tumor-associated antigens in the detection of ovarian cancer

In this study, enzyme-linked immunosorbent assay has been used to examine the frequencies of serum autoantibodies against two candidate tumor-associated antigens intensively selected from the Human Protein Atlas database, in combination with 13 tumor-associated antigens available from our lab in sera from 44 OC patients and 50 normal healthy controls. Conventional evaluation (mean + 3SD as the cutoff value to determine a positive reactivity), receiver operating characteristic curve analyses, and classification tree analysis were further used to evaluate the diagnostic performance of autoantibodies against these tumor-associated antigens (anti-tumor-associated antigens) in ovarian cancer. For single anti-tumor-associated antigen, when the cutoff values were set as mean + 3SD of normal healthy controls, NPM1, MDM2, PLAT, p53, and c-Myc could achieve sensitivity higher than 20% at 98% specificity. Combinational utilization of autoantibodies against MDM2, PLAT, NPM1, 14-3-3 Zeta, p53, and RalA achieved the optimal diagnostic performance with 72.7% sensitivity at 96% specificity. Receiver operating characteristic curve analysis showed that the area under the receiver operating characteristic curves of autoantibodies against c-Myc, NPM1, MDM2, p16, p53, and 14-3-3 Zeta were greater than 0.80. This indicated that these tumor-associated antigens held high potential to serve as diagnostic biomarkers in ovarian cancer detection. Decision tree analysis indicated that anti-c-Myc held high potential in the detection of ovarian cancer. Further studies are warranted to validate the diagnostic performance of these anti-tumor-associated antigens with high area under the receiver operating characteristic curve, including autoantibodies against c-Myc, MDM2, PLAT, NPM1, 14-3-3 Zeta, p53, and RalA.