Tumour-Associated Autoantibodies as Diagnostic Biomarkers for Breast Cancer: A Systematic Review and Meta-Analysis

Serum anti-CFL1, anti-EZR, and anti-CYPA autoantibody as diagnostic markers in ovarian cancer

The purpose of this study was to identify novel autoantibodies against tumor-associated antigens (TAAs) and explore a diagnostic panel for Ovarian cancer (OC). Enzyme-linked immunosorbent assay was used to detect the expression of five anti-TAA autoantibodies in the discovery (70 OC and 70 normal controls) and validation cohorts (128 OC and 128 normal controls). Machine learning methods were used to construct a diagnostic panel. Serum samples from 81 patients with benign ovarian disease were used to identify the specificity of anti-TAA autoantibodies for OC. In both the discovery and validation cohorts, the expression of anti-CFL1, anti-EZR, anti-CYPA, and anti-PFN1 was higher in patients with OC than that in normal controls. The area under the receiver operating characteristic curve, sensitivity, and specificity of the panel containing anti-CFL1, anti-EZR, and anti-CYPA were 0.762, 55.56%, and 81.31%. The panel identified 53.06%, 53.33%, and 51.11% of CA125 negative, HE4 negative and the Risk of Ovarian Malignancy Algorithm negative OC patients, respectively. The combination of the three anti-TAA autoantibodies can serve as a favorable diagnostic tool for OC and has the potential to be a complementary biomarker for CA125 and HE4 in the diagnosis of ovarian cancer.

Liquid biopsy in T-cell lymphoma: biomarker detection techniques and clinical application

T-cell lymphoma is a highly invasive tumor with significant heterogeneity. Invasive tissue biopsy is the gold standard for acquiring molecular data and categorizing lymphoma patients into genetic subtypes. However, surgical intervention is unfeasible for patients who are critically ill, have unresectable tumors, or demonstrate low compliance, making tissue biopsies inaccessible to these patients. A critical need for a minimally invasive approach in T-cell lymphoma is evident, particularly in the areas of early diagnosis, prognostic monitoring, treatment response, and drug resistance. Therefore, the clinical application of liquid biopsy techniques has gained significant attention in T-cell lymphoma. Moreover, liquid biopsy requires fewer samples, exhibits good reproducibility, and enables real-time monitoring at molecular levels, thereby facilitating personalized health care. In this review, we provide a comprehensive overview of the current liquid biopsy biomarkers used for T-cell lymphoma, focusing on circulating cell-free DNA (cfDNA), circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), Epstein-Barr virus (EBV) DNA, antibodies, and cytokines. Additionally, we discuss their clinical application, detection methodologies, ongoing clinical trials, and the challenges faced in the field of liquid biopsy.

Mucins as Potential Biomarkers for Early Detection of Cancer

Early detection significantly correlates with improved survival in cancer patients. So far, a limited number of biomarkers have been validated to diagnose cancers at an early stage. Considering the leading cancer types that contribute to more than 50% of deaths in the USA, we discuss the ongoing endeavors toward early detection of lung, breast, ovarian, colon, prostate, liver, and pancreatic cancers to highlight the significance of mucin glycoproteins in cancer diagnosis. As mucin deregulation is one of the earliest events in most epithelial malignancies following oncogenic transformation, these high-molecular-weight glycoproteins are considered potential candidates for biomarker development. The diagnostic potential of mucins is mainly attributed to their deregulated expression, altered glycosylation, splicing, and ability to induce autoantibodies. Secretory and shed mucins are commonly detected in patients' sera, body fluids, and tumor biopsies. For instance, CA125, also called MUC16, is one of the biomarkers implemented for the diagnosis of ovarian cancer and is currently being investigated for other malignancies. Similarly, MUC5AC, a secretory mucin, is a potential biomarker for pancreatic cancer. Moreover, anti-mucin autoantibodies and mucin-packaged exosomes have opened new avenues of biomarker development for early cancer diagnosis. In this review, we discuss the diagnostic potential of mucins in epithelial cancers and provide evidence and a rationale for developing a mucin-based biomarker panel for early cancer detection.

Cancer Is Associated with the Emergence of Placenta-Reactive Autoantibodies

Placenta-specific antigens are minimally expressed or unexpressed in normal adult tissues, while they are widely expressed in cancer. In the course of carcinogenesis, a vast array of autoantibodies (AAbs) is produced. Here, we used a quantitative approach to determine the reactivity of AAbs in the sera of patients with breast (BrC: N = 100, 100% female, median age: 51 years), gastric (GC: N = 30, 46.6% female, median age: 57 years), bladder (BC: N = 29, 34.4% female, median age: 57 years), and colorectal (CRC: N = 34, 41.1% female, median age: 51 years) cancers against first-trimester (FTP) and full-term placental proteome (TP) in comparison with age- and sex-matched non-cancer individuals. Human-on-human immunohistochemistry was used to determine reactive target cells in FTP. The effect of pregnancy on the emergence of placenta-reactive autoantibodies was tested using sera from pregnant women at different trimesters of pregnancy. Except for BC, patients with BrC (p < 0.0284), GC (p < 0.0002), and CRC (p < 0.0007) had significantly higher levels of placenta-reactive AAbs. BrC (p < 0.0001) and BC (p < 0.0409) in the early stages triggered higher autoantibody reactivity against FTP. The reactivities of BrC sera with FTP did not show an association with ER, PR, or HER2 expression. Pregnancy in the third trimester was associated with the induction of TP- and not FTP-reactive autoantibodies (=0.018). The reactivity of BrC sera with placental proteins was found to be independent of gravidity or abortion. BrC sera showed a very strong and specific pattern of reactivity with scattered cells beneath the syncytiotrophoblast layer. Our results reinforce the concept of the coevolution of placentation and cancer and shed light on the future clinical application of the placental proteome for the non-invasive early detection and treatment of cancer.

Autoantibodies as biomarkers for breast cancer diagnosis and prognosis

Breast cancer is the most common cancer in women worldwide and is a substantial public health problem. Screening for breast cancer mainly relies on mammography, which leads to false positives and missed diagnoses and is especially non-sensitive for patients with small tumors and dense breasts. The prognosis of breast cancer is mainly classified by tumor, node, and metastasis (TNM) staging, but this method does not consider the molecular characteristics of the tumor. As the product of the immune response to tumor-associated antigens, autoantibodies can be detected in peripheral blood and can be used as noninvasive, presymptomatic, and low-cost biomarkers. Therefore, autoantibodies can provide a possible supplementary method for breast cancer screening and prognosis classification. This article introduces the methods used to detect peripheral blood autoantibodies and the research progress in the screening and prognosis of breast cancer made in recent years to provide a potential direction for the examination and treatment of breast cancer.

Can serum autoantibodies be a potential early detection biomarker for breast cancer in women? A diagnostic test accuracy review and meta-analysis

BACKGROUND

The increasing incidence of breast cancer necessitates the need to explore alternate screening strategies that circumvent the setbacks of conventional techniques especially among population that report earlier age at diagnosis. Serum autoantibodies is one such potential area of interest. However, their ubiquitous presence across cancer types limits its applicability to any one specific type of cancer. This review was therefore carried out to explore and consolidate available evidence on autoantibodies for early detection of breast cancer and to identify those that demonstrated a higher sensitivity.

METHODS

A diagnostic test accuracy (DTA) review was carried out to ascertain serum autoantibodies that could be used for early detection of breast cancer among women. All relevant articles that investigated the role of autoantibodies in early detection of breast cancer were included for the review. MEDLINE, Scopus, ProQuest, Ovid SP, and Cochrane Library were searched extensively for eligible studies. Quality of the included studies was assessed using Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 tool. RevMan 5.3 was used for exploratory and MetaDTA 2019 for hierarchical analyses. The review helped identify the most frequently investigated autoantibodies and a meta-analysis further consolidated the findings.

RESULTS

A total of 53 articles were included for the final analysis that reported over a 100 autoantibodies that were studied for early detection of breast cancer in women. P53, MUC1, HER2, HSP60, P16, Cyclin B1, and c-Myc were the most frequently investigated autoantibodies. Of these P53, MUC1, HER2, and HSP60 exhibited higher summary sensitivity measures. While the individual pooled sensitivity estimates ranged between 10 and 56%, the panel sensitivity values reported across studies were higher with an estimated range of 60-87%.

CONCLUSION

Findings from the review indicate a higher sensitivity for an autoantibody panel in comparison to individual assays. A panel comprising of P53, MUC1, HER2, and HSP60 autoantibodies has the potential to be investigated as an early detection biomarker for breast cancer.

Meta-analysis of diagnostic cell-free circulating microRNAs for breast cancer detection

Background

Breast cancer (BC) is the most frequently diagnosed cancer among women. Numerous studies explored cell-free circulating microRNAs as diagnostic biomarkers of BC. As inconsistent and rarely intersecting microRNA panels have been reported thus far, we aim to evaluate the overall diagnostic performance as well as the sources of heterogeneity between studies.

Methods

Based on the search of three online search engines performed up to March 21^st 2022, 56 eligible publications that investigated diagnostic circulating microRNAs by utilizing Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) were obtained. Primary studies’ potential for bias was evaluated with the revised tool for the quality assessment of diagnostic accuracy studies (QUADAS-2). A bivariate generalized linear mixed-effects model was applied to obtain pooled sensitivity and specificity. A novel methodology was utilized in which the sample and study models’ characteristics were analysed to determine the potential preference of studies for sensitivity or specificity.

Results

Pooled sensitivity and specificity of 0.85 [0.81—0.88] and 0.83 [0.79—0.87] were obtained, respectively. Subgroup analysis showed a significantly better performance of multiple (sensitivity: 0.90 [0.86—0.93]; specificity: 0.86 [0.80—0.90]) vs single (sensitivity: 0.82 [0.77—0.86], specificity: 0.83 [0.78—0.87]) microRNA panels and a comparable pooled diagnostic performance between studies using serum (sensitivity: 0.87 [0.81—0.91]; specificity: 0.83 [0.78—0.87]) and plasma (sensitivity: 0.83 [0.77—0.87]; specificity: 0.85 [0.78—0.91]) as specimen type. In addition, based on bivariate and univariate analyses, miRNA(s) based on endogenous normalizers tend to have a higher diagnostic performance than miRNA(s) based on exogenous ones. Moreover, a slight tendency of studies to prefer specificity over sensitivity was observed.

Conclusions

In this study the diagnostic ability of circulating microRNAs to diagnose BC was reaffirmed. Nonetheless, some subgroup analyses showed between-study heterogeneity. Finally, lack of standardization and of result reproducibility remain the biggest issues regarding the diagnostic application of circulating cell-free microRNAs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09698-8.

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.

The implication of autoantibodies in early diagnosis and monitoring of plasmonic photothermal therapy in the treatment of feline mammary carcinoma

Feline mammary carcinoma (FMC) shows great similarities to human breast cancer in the cellular and molecular levels. So, in cats as in humans, the role of immune responses is indicated to detect and follow up the development of tumors. As a new breast cancer therapeutic approach, Plasmonic Photothermal Therapy (PPTT) is an effective localized treatment for canine and feline mammary-carcinoma. Its systemic effect has not been inquired yet and needs many studies to hypothesis how the PPTT eradicates tumor cells. In this study, it is the first time to detect (P53, PCNA, MUC-1, and C-MYC) feline autoantibodies (AAbs), study the relationship between PCNA AAbs and mammary-tumors, and investigate the effect of PPTT on the humoral immune response of cats with mammary-carcinoma through detection of AAbs level before, during, and after the treatment. The four-AAbs panel was evaluated in serum of normal and clinically diagnosed cats with mammary tumors using Enzyme-Linked Immunosorbent Assay. The panel showed 100% specificity and 93.7% sensitivity to mammary tumors. The panel was evaluated in PPTT monotherapy, mastectomy monotherapy, and combination therapy. PPTT monotherapy decreased AAbs level significantly while mastectomy monotherapy and combination therapy had a nonsignificant effect on AAbs level.

Immunoassay detection of tumor-associated autoantibodies using protein G bioconjugated to nanomagnet-silica decorated with Au@Pd nanoparticles

A colorimetric immunosensor was developed for the detection of tumor-associated anti-p53 autoantibodies (anti-p53aAbs). The immunosensor platform was prepared by immobilizing human-protein (p53Ag) onto a high binding 96-well plate. The immunoassay was based on the immunometric sandwich protocol, and protein G functionalized nanomagnet-silica nanoparticles decorated with Au@Pd (Fe₃O₄@SiO₂-NH₂-Au@Pd_0.30NPs-protG) was used as the detection nanobioprobe. The Fe₃O₄@SiO₂-NH₂-Au@Pd_0.30NPs-protG exhibited a high binding affinity for the captured anti-p53aAbs and high catalytic performance towards the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB). The oxidation of TMB resulted in significant color change and a UV-vis absorption signal. The detection was achieved by measuring the changes in UV-Vis absorption as the concentrations of anti-p53aAbs changed. The apparent binding affinity (K_D) between the p53aAbs and Fe₃O₄@SiO₂-NH₂-Au@Pd_0.30NPs-protG was 35.2 ng mL^-1. The plot of change in the absorption intensity against the logarithm of anti-p53aAbs was linear within 1.0-500.0 ng mL^-1 with a correlation coefficient (R²) of 0.98. The detection limit (LoD) using 3σ was calculated to be 15 pg mL^-1, which is lower than the conventional HRP-label based colorimetric immunoassay. The real sample detection was investigated using the serum recovery method. The recovery of the anti-p53aAbs ranges from 98.5% to 105.7%, demonstrating its potential for practical applications.

Enhanced humoral immunity in breast cancer patients with high serum concentration of anti-HER2 autoantibody

Humoral immunity plays a substantial role in the suppression of breast cancer. We have revealed that a high serum concentration of anti‐HER2 autoantibody (HER2‐AAb) is associated with favorable outcomes in patients with invasive breast cancer. Thus, we aimed to clarify the association between high serum concentration of HER2‐AAb and humoral immune response in the tumor microenvironment. Out of 500 consecutive patients with invasive breast cancer, we selected those whose HER2‐AAb values were high (n = 33) or low (n = 20) based on the distribution of HER2‐AAb values of 100 healthy individuals. Tumor and regional lymph node formalin‐fixed paraffin‐embedded samples prepared from the surgical specimens were subjected to immunohistochemistry. We confirmed that the recurrence‐free survival of the high HER2‐AAb group was significantly longer than that of the low HER2‐AAb group (p = 0.015). The numbers of tumor‐infiltrating CD20+ immune cells (ICs) (p < 0.001), IGKC+ICs (p = 0.023), and CXCL13+ ICs (p = 0.044) were significantly higher in the high HER2‐AAb group than in the low HER2‐AAb group. The number of CD4+ ICs in the B‐cell follicles of the regional lymph nodes was also significantly greater in the high HER2‐AAb group than in the low HER2‐AAb group (p = 0.026). Our findings indicate that a high level of HER2‐AAb is associated with enhanced humoral immunity against breast cancer and thus may provide a rationale for the association of HER2‐AAb with favorable prognosis.

Recent Discoveries of Macromolecule- and Cell-Based Biomarkers and Therapeutic Implications in Breast Cancer

Breast cancer is the most commonly diagnosed cancer type and the leading cause of cancer-related mortality in women worldwide. Breast cancer is fairly heterogeneous and reveals six molecular subtypes: luminal A, luminal B, HER2+, basal-like subtype (ER−, PR−, and HER2−), normal breast-like, and claudin-low. Breast cancer screening and early diagnosis play critical roles in improving therapeutic outcomes and prognosis. Mammography is currently the main commercially available detection method for breast cancer; however, it has numerous limitations. Therefore, reliable noninvasive diagnostic and prognostic biomarkers are required. Biomarkers used in cancer range from macromolecules, such as DNA, RNA, and proteins, to whole cells. Biomarkers for cancer risk, diagnosis, proliferation, metastasis, drug resistance, and prognosis have been identified in breast cancer. In addition, there is currently a greater demand for personalized or precise treatments; moreover, the identification of novel biomarkers to further the development of new drugs is urgently needed. In this review, we summarize and focus on the recent discoveries of promising macromolecules and cell-based biomarkers for the diagnosis and prognosis of breast cancer and provide implications for therapeutic strategies.

A Panel of Tumor-associated Autoantibodies for the Detection of Early-stage Breast Cancer

We previously found a panel of autoantibodies against multiple tumor-associated antigens (BMI-1, HSP70, MMP-7, NY-ESO-1, p53 and PRDX6) that might facilitate early detection of esophagogastric junction adenocarcinoma and esophageal squamous cell carcinoma. Here we aimed at assessing the diagnostic performance of these autoantibodies in breast cancer patients. Enzyme-linked immunosorbent assay was applied to detect sera autoantibodies in 123 breast cancer patients and 123 age-matched normal controls. We adopted logistic regression analysis to identify optimized autoantibody biomarkers for diagnosis and receiver-operating characteristics to analyze diagnostic efficiency. Five of six autoantibodies, BMI-1, HSP70, NY-ESO-1, p53 and PRDX6 demonstrated significantly elevated serum levels in breast cancer compared to normal controls. An optimized panel composed of autoantibodies to BMI-1, HSP70, NY-ESO-1 and p53 showed an area under the curve (AUC) of 0.819 (95% CI 0.766-0.873), 63.4% sensitivity and 90.2% specificity for diagnosing breast cancer. Moreover, this autoantibody panel could differentiate patients with early stage breast cancer from normal controls, with AUC of 0.805 (95% CI 0.743-0.886), 59.6% sensitivity and 90.2% specificity. Our findings indicated that the panel of autoantibodies to BMI-1, HSP70, NY-ESO-1 and p53 as serum biomarkers have the potential to help detect early stage breast cancer.

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.

Serum Analysis of Women with Early-Stage Breast Cancer Using a Mini-Array of Tumor-Associated Antigens

Background: Several studies have shown that patients with cancer have antibodies in serum that react with cellular autoantigens, known as Tumor-Associated Antigens (TAA). The present work aimed to determine whether a mini-array comprising four recombinant TAA increases the detection of specific serum antibodies for the diagnosis of early-stage breast cancer. Methods: The mini-array included Alpha 1-AntiTrypsin (A1AT), TriosePhosphate Isomerase 1 (TPI1), Peptidyl-Prolyl cis-trans Isomerase A (PPIA), and PeroxiReDoXin 2 (PRDX2) full-length recombinant proteins. The proteins were produced after gene cloning, expression, and purification, and were verified by Western blot assays. Then, Dot-Blot was performed to find antibodies against the four TAA in 12 sera from women with early-stage breast cancer (stage II) and 12 sera from healthy women. Results: Antibody detection against individual TAA in early-stage breast cancer sera ranged from 58.3% to 83.3%. However, evaluation of the four TAA showed that there was a positive antibody reaction reaching a sensitivity of 100% and a specificity of 85% in early-stage breast cancer, suggesting that this mini-array must be evaluated as a clinical diagnostic tool for early-stage breast cancer in a larger sample size. Conclusion: Our results suggest that TAA mini-arrays may provide a promising and powerful method for improving the detection of breast cancer in Mexican women.

Diagnostic value of seven biomarkers for breast cancer: an overview with evidence mapping and indirect comparisons of diagnostic test accuracy

Several meta-analyses have evaluated the value of biomarkers in diagnosing breast cancer, but which biomarker has the optimal diagnostic value remains unclear. This overview aimed to compare the accuracy of different biomarkers in diagnosing breast cancer. PubMed, Embase.com, the Cochrane Library of Systematic Reviews, and Web of Science were searched. The assessment of multiple systematic reviews-2 (AMSTAR-2) was used to assess the methodological quality and preferred reporting items for a systematic review and meta-analysis of diagnostic test accuracy (PRISMA-DTA) for reporting quality. Pairwise meta-analyses were performed to estimate the pooled results for each biomarker, and indirect comparisons were conducted to compare diagnostic accuracy between biomarkers. Eleven systematic reviews (SRs) involving 218 original studies were included. All SRs were of critically low methodological quality, 3 SRs had minimal reporting flaws and 8 SRs had minor flaws. The pooled sensitivity and specificity were 0.77 and 0.87 for miRNA, 0.70 and 0.87 for circulating cell-free DNA, 0.29 and 0.96 for APC gene promoter methylation, 0.69 and 0.99 for 14-3-3σ promoter methylation, 0.63 and 0.82 for CA153, 0.58 and 0.87 for CEA, and 0.73 and 0.56 for PSA. Compared with CA153 and PSA, miRNA had a higher sensitivity and specificity. The sensitivity of miRNA was higher than circulating cell-free DNA and CEA, although they had the same specificities. APC gene promoter methylation and 14-3-3σ promoter methylation were more specific than miRNA, but they had unacceptably low sensitivity. In conclusion, miRNA had better diagnostic accuracy than the other six biomarkers. But due to the low quality of included SRs, the results need to be interpreted with caution. Further study should investigate the diagnostic accuracy of different biomarkers in direct comparisons and focus on the value of combined biomarkers.

Current immunoassay methods and their applications to clinically used biomarkers of breast cancer

Breast cancer is the leading cause of cancer-related mortality worldwide, with a higher incidence in developed countries. The biomarkers for breast cancer such as estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, CA (cancer antigen) 15-3, CA 27.29, and carcinoembryonic antigen have been recommended for use in the laboratory based on the guidelines of American and European societies. Immunoassays have been frequently and consistently used to detect these clinically established biomarkers of breast cancer. Despite the higher accessibility of serum biomarkers, including CA 15-3, CA 27.29, and CEA, compared to tissue markers, variations in immunoassays affect their standardization and clinical utility. When reviewing the immunoassays used to detect these serum markers, we found that the most frequently used immunoassay was enzyme-linked immunosorbent assay, followed by electrochemiluminescent immunoassay, and then chemiluminescence immunoassay for CA 15-3 and CEA. Meanwhile, the chemiluminescence immunoassay was the most common technique for CA27.29. The electrochemiluminescent immunoassay and monoclonal fluorometric assay have become the preferred methods in 2010-2019 compared to 2000-2009. Analytical and clinical performance factors such as sensitivity, specificity, detection limit, hazard risk to laboratory personnel, speed, and economic feasibility influenced these changes in user preference. When using the immunoassays, there should be a comprehensive understanding of the principles, advantages, vulnerability, and precautions for interpretation. In the future, a combination of immunological biomarkers and genetic platforms will benefit patients with breast cancer by facilitating prognosis prediction and guiding therapeutic intervention.

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 Potential Biomarkers in Breast Cancer

Breast cancer is a major cause of mortality in women; however, technologies for early stage screening and diagnosis (e.g., mammography and other imaging technologies) are not optimal for the accurate detection of cancer. This creates demand for a more effective diagnostic means to replace or be complementary to existing technologies for early discovery of breast cancer. Cancer neoantigens could reflect tumorigenesis, but they are hardly detectable at the early stage. Autoantibodies, however, are biologically amplified and hence may be measurable early on, making them promising biomarkers to discriminate breast cancer from healthy tissue accurately. In this review, we summarized the recent findings of breast cancer specific antigens and autoantibodies, which may be useful in early detection, disease stratification, and monitoring of treatment responses of breast cancer.

Trial watch: DNA-based vaccines for oncological indications

DNA-based vaccination is a promising approach to cancer immunotherapy. DNA-based vaccines specific for tumor-associated antigens (TAAs) are indeed relatively simple to produce, cost-efficient and well tolerated. However, the clinical efficacy of DNA-based vaccines for cancer therapy is considerably limited by central and peripheral tolerance. During the past decade, considerable efforts have been devoted to the development and characterization of novel DNA-based vaccines that would circumvent this obstacle. In this setting, particular attention has been dedicated to the route of administration, expression of modified TAAs, co-expression of immunostimulatory molecules, and co-delivery of immune checkpoint blockers. Here, we review preclinical and clinical progress on DNA-based vaccines for cancer therapy.

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.

Systematic review: Tumor-associated antigen autoantibodies and ovarian cancer early detection

OBJECTIVES

Tumor-associated autoantibodies (AAbs), produced as an immune response to tumor-associated antigens (TAAs), are a novel pathway of early detection markers.

METHODS

We conducted a systematic review on AAbs and ovarian cancer to summarize the diagnostic performance of individual AAbs and AAb panels. A total of 29 studies including 85 AAbs were included; 27 of the studies were conducted in prevalent cases and cancer-free controls and 2 investigations included pre-diagnosis samples. The majority of studies were hypothesis-driven, evaluating AAbs to target TAAs; 10 studies used screening approaches such as serological expression cloning (SEREX) and nucleic acid-programmable protein arrays (NAPPA).

RESULTS

The highest sensitivities for individual AAbs were reported for RhoGDI-AAbs (89.5%) and TUBA1C-AAbs (89%); however, specificity levels were relatively low (80% and 75%, respectively). High sensitivities at high specificities were reported for HOXA7-AAbs for detection of moderately differentiated ovarian tumors (66.7% sensitivity at 100% specificity) and IL8-AAbs in stage I-II ovarian cancer (65.5% sensitivity at 98% specificity). A panel of 11 AAbs (ICAM3, CTAG2, p53, STYXL1, PVR, POMC, NUDT11, TRIM39, UHMK1, KSR1, and NXF3) provided 45% sensitivity at 98% specificity for serous ovarian cancer, when at least 2 AAbs were above a threshold of 95% specificity. Twelve of the AAbs identified in this review were investigated in more than one study. Data on diagnostic discrimination by tumor histology and stage at diagnosis are sparse. Limited data suggest select AAb markers improve diagnostic discrimination when combined with markers such as CA125 and HE4.

CONCLUSIONS

AAbs for ovarian cancer early detection is an emerging area, and large-scale, prospective investigations considering histology and stage are required for discovery and validation. However, data to date suggests panels of AAbs may eventually reach sufficient diagnostic discrimination to allow earlier detection of disease as a complement to existing markers and transvaginal ultrasound.

Rethinking Autoantibody Signature Panels for Cancer Diagnosis

INTRODUCTION

Most pulmonary nodules found on imaging studies are indeterminate, but because of the concern for lung cancer, all patients require further evaluation with resultant radiation risk, significant cost, and delays in diagnosis. We hypothesized that a diagnostic blood test based on detection of autoantibodies against cancer antigens would be able to distinguish a benign nodule from lung cancer.

METHODS

We identified a panel of 25 serum autoantibodies associated with NSCLC and constructed a protein microarray containing the autoantigens. We tested the microarray with human sera (from 125 patients with NSCLC and 125 matched controls with a benign nodule) and attempted to develop a classification algorithm that would separate the two groups.

RESULTS

In the training data set the logistic regression c-index statistic was 0.691; in the validation data set, the model predicting the score generated from the training set model had a c-index of 0.490. The relationship between the score and outcome (final diagnosis) was not statistically significant (p = 0.460).

CONCLUSIONS

When the current panel of antigens and assay format was used, classification algorithms based on levels of autoantibodies to cancer antigens did not prove to have statistically significant value for predicting the presence of cancer. We suggest that there are inherent biological limitations to this approach.