Alpha 1-antitrypsin: a novel tumor-associated antigen identified in patients with early-stage breast cancer

Autoantibody Recognition of Natural and Homocysteinylated Alpha-1 Antitrypsin: Indirect Enzyme-Linked Immunosorbent Assay (ELISA) Quantification in Sera

In this chapter, indirect enzyme-linked immunosorbent assays (ELISAs) to quantitatively measure autoantibodies directed to human natural and homocysteinylated alpha-1 antitrypsin (anti-AATA and anti-HAATA, respectively) in serum are described. The illustrated ELISA protocols are slightly different, since the two protein forms have different biochemical features and, consequently, different affinity for the matrix (polystyrene microplate wells), so that specific experimental conditions have to be performed for the quantification of the serum antibody recognition.These procedures can be carried out to evaluate the anti-AATA and the anti-HAATA levels, testing serum samples, for research use.

Autoantibody Diversity Is Augmented in Women with Breast Cancer and Is Related to the Stage of the Disease

Breast cancer (BC) is the most frequent malignant neoplasia and leading cause of cancer mortality for women. A timely diagnosis of BC is crucial to ensure the best chances of survival. Among the various screening tools for BC, antibodies directed towards self-antigens or tumor-associated antigens (autoantibodies) have emerged as an alternative to image-based screening modalities. However, little attention has been paid to the global diversity of autoantibodies. This work aimed to analyze the diversity of autoantibodies reactive to antigens expressed by the BC cell line T47D in the sera of Mexican women with BC, benign breast pathology (BBP), or without breast pathology (WBP). We found that the diversity of antibodies in the sera was higher in the BC and BBP groups than in the WBP group. Likewise, the diversity changed with the progression of BC. Our results show and measure the complexity of the antibody response in breast health and disease.

Serpin Family A Member 1 Is Prognostic and Involved in Immunological Regulation in Human Cancers

Serpin family A member 1 (SERPINA1) encodes a protease inhibitor participating in many human diseases, but its value in immunoregulation and prognosis of human cancers remains unclear. In this study, through comprehensive analysis of data from The Cancer Genome Atlas (TCGA) datasets, we found that SERPINA1 was dysregulated in many cancers compared with normal tissues. SERPINA1 expression was significantly associated with prognosis, immune subtype, molecular subtype, immune checkpoint (ICP) genes, tumor mutational burden (TMB), microsatellite instability (MSI), and the estimation of stromal and immune cells in malignant tumor tissues using expression data (ESTIMATE) score. There was a strong connection between SERPINA1 expression and tumor-infiltrating lymphocytes, and SERPINA1 showed significant relation to gene markers of immune cells in digestive tumors. Fluorescence-based multiplex immunohistochemistry confirmed that SERPINA1 protein expression was related to clinicopathologic features and immune infiltrates in hepatic cancer. This study suggests that SERPINA can potentially serve as a novel biomarker for cancer prognosis and immunotherapy.

Breast cancer in the era of integrating “Omics” approaches

Worldwide, breast cancer is the leading cause of cancer-related deaths in women. Breast cancer is a heterogeneous disease characterized by different clinical outcomes in terms of pathological features, response to therapies, and long-term patient survival. Thus, the heterogeneity found in this cancer led to the concept that breast cancer is not a single disease, being very heterogeneous both at the molecular and clinical level, and rather represents a group of distinct neoplastic diseases of the breast and its cells. Indubitably, in the past decades we witnessed a significant development of innovative therapeutic approaches, including targeted and immunotherapies, leading to impressive results in terms of increased survival for breast cancer patients. However, these multimodal treatments fail to prevent recurrence and metastasis. Therefore, it is urgent to improve our understanding of breast tumor and metastasis biology. Over the past few years, high-throughput “omics” technologies through the identification of novel biomarkers and molecular profiling have shown their great potential in generating new insights in the study of breast cancer, also improving diagnosis, prognosis and prediction of response to treatment. In this review, we discuss how the implementation of “omics” strategies and their integration may lead to a better comprehension of the mechanisms underlying breast cancer. In particular, with the aim to investigate the correlation between different “omics” datasets and to define the new important key pathway and upstream regulators in breast cancer, we applied a new integrative meta-analysis method to combine the results obtained from genomics, proteomics and metabolomics approaches in different revised studies.

BH-index: A predictive system based on serum biomarkers and ensemble learning for early colorectal cancer diagnosis in mass screening

BACKGROUND AND OBJECTIVE

Colorectal cancer is one of the most common malignancies among the general population. Artificial Intelligence methodologies based on serum parameters are in continuous development to obtain less expensive tools for highly sensitive diagnoses. This study proposes a predictive system based on serum biomarkers and ensemble learning to predict colorectal cancer presence and the related TNM stage in patients.

METHODS

We have selected 17 significant plasmatic proteins, i.e., Carcinoembryonic Antigen, CA 19-9, CA 125, CA 50, CA 72-4, Tissue Polypeptide Antigen, C-Reactive Protein, Ceruloplasmin, Haptoglobin, Transferrin, Ferritin, α-1-Antitrypsin, α-2-Macroglobulin, α-1 Acid Glycoprotein, Complement C4, Complement C3, and Retinol Binding Protein, regarding 345 patients (248 affected by the neoplastic disease). The proposed system consists of two predictors, i.e., binary and staging; the former predicts the presence/absence of cancer, while the latter identifies the related TNM stage (I, II, III, or IV). The experiments were conducted by deploying and comparing Random Forest, XGBoost, Support Vector Machine, and Multilayer Perceptron with feature selection based on Gini Importance and with dimensionality reduction via PCA.

RESULTS

The results show that the system composed of XGBoost as binary and staging predictor reaches 91.30% accuracy, 90% sensitivity, and 93.33% specificity for the absence/presence outcome, while 66.66% accuracy for the staging response. With the expansion of the training set in favor of positive patients and majority voting, the system composed of the combination of Support Vector Machine, XGBoost, and Multilayer Perceptron as the binary predictor reaches 98.03% accuracy, 100% sensitivity, and 92.30% specificity, while the combination of Random Forest, XGBoost, and Multilayer Perceptron as staging predictor achieves 60% accuracy. The final system reaches, in terms of accuracy, 98.03%, and 66.66% for the binary and staging predictors, respectively. It was also found that the biomarkers which contribute most to the binary decision are Ceruloplasmin and α-2-Macroglobulin, while the least significant dimensions are CA 50 and α-1-Antitrypsin; instead, Carcinoembryonic Antigen and α-1 Acid Glycoprotein are the most significant to the staging decision.

CONCLUSIONS

The present study proves the effectiveness of deploying serum biomarkers as feature dimensions for early colorectal cancer diagnosis and of using majority voting for noise reduction in the prediction.

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.

Autoantibodies in Early Detection of Breast Cancer

In spite of the progress made in treatment and early diagnosis, breast cancer remains a major public health issue worldwide. Although modern image-based screening modalities have significantly improved early diagnosis, around 15% to 20% of breast cancers still go undetected. In underdeveloped countries, lack of resources and cost concerns prevent implementing mammography for routine screening. Noninvasive, low-cost, blood-based markers for early breast cancer diagnosis would be an invaluable alternative that would complement mammography screening. Tumor-specific autoantibodies are excellent biosensors that could be exploited to monitor disease-specific changes years before disease onset. Although clinically informative autoantibody markers for early breast cancer screening have yet to emerge, progress has been made in the development of tools to discover and validate promising autoantibody signatures. This review focuses on the current progress toward the development of autoantibody-based early screening markers for breast cancer.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

Inhibition of miR‑214 attenuates the migration and invasion of triple‑negative breast cancer cells

Triple‑negative breast cancer (TNBC) is a subtype of breast cancer. MicroRNA (miR)‑214 is closely associated with controlling the development of tumor cells; therefore, in the present study, the target gene and effects of miR‑214 on TNBC cells were explored. Luciferase activity was examined by luciferase reporter assay. The viability, invasion and migration of MDA‑MB‑231 TNBC cells were measured using Cell Counting kit‑8, Transwell and wound‑healing assays, respectively. The expression levels of various factors were determined using reverse transcription‑quantitative polymerase chain reaction and western blotting. The results demonstrated that the expression levels of miR‑214 were higher and the levels of α1‑antitrypsin (α1‑AT) were lower in TNBC tissues compared with in normal tissues. Subsequently, α1‑AT was revealed to be a target of miR‑214. Furthermore, inhibition of miR‑214 decreased cell viability, invasion and migration, enhanced the expression of E‑cadherin and tissue inhibitor of metalloproteinases‑2, and reduced the expression of metastatic tumour antigen 1 and matrix metalloproteinase‑2. Inhibition of miR‑214 also significantly downregulated the phosphorylation of protein kinase B (Akt) and mammalian target of rapamycin (mTOR), and markedly downregulated that of phosphoinositide 3‑kinase (PI3K); however, the expression levels of total PI3K, Akt and mTOR remained stable in all groups. Taken together, these findings indicated that α1‑AT may be a target of miR‑214. Downregulation of miR‑214 markedly suppressed the viability, migration and invasion of MDA‑MB‑231 cells, and inhibited the PI3K/Akt/mTOR pathway. These findings suggested that miR‑214 targeting α1‑AT may be a potential mechanism underlying TNBC development.

Estudio proteómico 2DE-DIGE en plasma sanguíneo de pacientes en etapa infantil con leucemia linfoblástica aguda

En Colombia, durante la última década la leucemia linfoblástica aguda (LLA) ha sido el cáncer con mayor incidencia, siendo más del 40% de las muertes por cáncer en menores de edad atribuidas a esta enfermedad. Entre los factores que influyen en estas cifras, el diagnóstico tardío es tal vez el factor más sensible que afecta de manera negativa el éxito del tratamiento. Esta investigación se centró en el estudio del proteoma plasmático de niños colombianos diagnosticados con LLA tipo B, dada su alta incidencia, en comparación con controles en la búsqueda de proteínas que podrían tener potencialidad a ser clasificadas como biomarcadores de diagnóstico. Ahora bien, en vista de los avances en las herramientas proteómicas y de espectrometría de masas y sabiendo que son una alternativa para abordar la complejidad molecular de enfermedades como el cáncer, utilizamos una aproximación proteómica basada en una separación por electroforesis bidimensional diferencial (2DE-DIGE) con posterior separación por cromatografía líquida acoplada a espectrometría de masas en tándem. Se encontraron 8 proteínas con expresión diferencial en plasma de pacientes con LLA-B, entre las cuales resaltan la serotransferrina, la Alfa-1-antitripsina, la haptoglobina, la α2-glicoproteína de zinc y la complemento C3.

Silence of α1-Antitrypsin Inhibits Migration and Proliferation of Triple Negative Breast Cancer Cells

BACKGROUND α1-antitrypsin (α1-AT) is highly expressed in many tumors. However, to the best of our knowledge, its relationship to triple negative breast cancer (TNBC) has not yet been studied. Thus, in this research we first explored the influence of α1-AT silencing on the abilities of migration and invasion, and then further study its molecular mechanism in TNBC cells. MATERIAL AND METHODS The viability of MDA-MB-231 cells were detected using cell counting kit-8 (CCK-8). The abilities of migration and invasion were examined by Transwell assay. The metastasis-related factors were tested respectively by quantitative real-time PCR (qRT-PCR) and western blot assays. RESULTS Our study results showed that α1-AT level in TNBC tissues was higher than non-triple negative breast cancer (n-TNBC) and adjacent normal breast tissues. The high expression of α1-AT was linked to type of cancer, tumor size, TNM stage and metastasis, but was not correlated with α1-AT expression and age. si-α1-AT suppressed the viability, migration, and invasion of cells. While si-α1-AT upregulated E-cadherin and the tissue inhibitor of metalloproteinases-2 (TIMP-2) levels, it downregulated metastasis associated 1 (MTA1), matrix metallopeptidase 2 (MMP2), phosphorylated-mammalian target of rapamycin (p-mTOR), phosphorylated-protein kinase B (p-Akt), and phosphorylated-phosphatidylinositol 3 kinase (p-PI3K) levels. We also found that the PI3K/Akt/mTOR pathway activator reversed the role of si-α1-AT in metastasis-related factors. CONCLUSIONS α1-AT was highly expressed in TNBC tissues, and its silencing suppressed the abilities of migration and invasion in TNBC cells and downregulated the PI3K/Akt/mTOR pathway. Thus, α1-AT may have a potential therapeutic effect on TNBC.

Longitudinal autoantibody responses against tumor-associated antigens decrease in breast cancer patients according to treatment modality

BACKGROUND

Metastatic breast cancer (BCa) is most often diagnosed months after completion of treatment of the primary tumor when a patient reports physical symptoms. Besides a physical examination, no other alternative recurrence screening method is recommended for routine follow-up care. Detection of autoantibodies against tumor-associated antigens (TAAs) has demonstrated promise for distinguishing healthy women from patients diagnosed with primary BCa. However, it is unknown what changes occur to patient autoantibody levels during and after treatment.

METHODS

Three serial blood draws were collected from 200 BCa patients: before treatment, 6 and 12 months after surgery. Patients were categorized according to treatment regimen, including surgery, chemotherapy, radiation, trastuzumab and hormonal therapies. The longitudinal samples were assayed for autoantibody responses against 32 conformation-carrying TAAs using a Luminex multiplex bead assay.

RESULTS

The treatment modality groups that had the greatest decrease in autoantibody response levels were radiation + hormonal therapy; radiation + chemotherapy; and radiation + hormonal therapy + chemotherapy. For these three treatment groups, autoantibody responses against 9 TAAs (A1AT, ANGPTL4, CAPC, CST2, DKK1, GFRA1, GRN, LGALS3 and LRP10) were significantly reduced at 12 months after surgery compared to before treatment. One TAA, GRP78, had a significantly increased autoantibody response after 12 months.

CONCLUSIONS

Single treatment regimens alone did not significantly alter autoantibodies levels against the studied TAAs. Radiation treatment was the common denominator of the three most affected groups for significant changes in autoantibody response levels.

Identification of liver metastasis-associated genes in human colon carcinoma by mRNA profiling

Objective

Liver metastasis, which contributes substantially to high mortality, is the most common recurrent mode of colon carcinoma. Thus, it is necessary to identify genes implicated in metastatic colonization of the liver in colon carcinoma.

Methods

We compared mRNA profiling in 18 normal colon mucosa (N), 20 primary tumors (T) and 19 liver metastases (M) samples from the dataset GSE49355 and GSE62321 of Gene Expression Omnibus (GEO) database. Gene ontology (GO) and pathways of the identified genes were analyzed. Co-expression network and protein-protein interaction (PPI) network were employed to identify the interaction relationship. Survival analyses based on The Cancer Genome Atlas (TCGA) database were used to further screening. Then, the candidate genes were validated by our data.

Results

We identified 22 specific genes related to liver metastasis and they were strongly associated with cell migration, adhesion, proliferation and immune response. Simultaneously, the results showed that C-X-C motif chemokine ligand 14 (CXCL14) might be a favorable prediction factor for survival of patients with colon carcinoma. Importantly, our validated data further suggested that lower CXCL14 represented poorer outcome and contributed to metastasis. Gene set enrichment analysis (GSEA) showed that CXCL14 was negatively related to the regulation of stem cell proliferation and epithelial to mesenchymal transition (EMT).

Conclusions

CXCL14 was identified as a crucial anti-metastasis regulator of colon carcinoma for the first time, and might provide novel therapeutic strategies for colon carcinoma patients to improve prognosis and prevent metastasis.

SERPINA1 is a direct estrogen receptor target gene and a predictor of survival in breast cancer patients

Of all breast cancer patients, about 70% are ER+ and 10% are ER+/HER2+. The ER+/HER2+ patients have a worse outcome compared to ER+/HER2- patients. Currently there is a lack of effective prognosis biomarkers for the prediction of outcome in ER+/HER2+ patients. Genome-wide differences in ER binding between the endocrine-responsive and endocrine-resistant cells were discovered using ChIP-seq, and combined with gene expression microarray data to identify direct ER target genes. These genes were correlated to survival outcome using publicly available breast cancer patient cohorts. We found the expression of the gene SERPINA1 to have a significant predictive value for the overall survival (OS) of ER+ patients in the TCGA cohort, and validated this finding in the Curtis cohort. SERPINA1 also has a significant predictive value for the OS of ER+/HER2+ patients in the TCGA cohort, with validation in the Bild cohort. The expression of SERPINA1 can be suppressed by fulvestrant and HER2 siRNA. Our results indicate that ER is constitutively activated, resulting in an E2-independent ER binding to the SERPINA1 gene and upregulation of SERPINA1 expression. Importantly, results of survival correlation suggests that high expression of SERPINA1 could be predictive for a better clinical outcome of ER+ and ER+/HER2+ patients.

Crucial considerations for pipelines to validate circulating biomarkers for breast cancer

Despite decades of progress in breast imaging, breast cancer remains the second most common cause of cancer mortality in women. The rapidly proliferative breast cancers that are associated with high relapse rates and mortality frequently present in younger women, in unscreened individuals, or in the intervals between screening mammography. Biomarkers exist for monitoring metastatic disease, such as CEA, CA27.29 and CA15-3, but there are no circulating biomarkers clinically available for early detection, prognosis, or monitoring for clinical relapse. There has been significant progress in the discovery of potential circulating biomarkers, including proteins, autoantibodies, nucleic acids, exosomes, and circulating tumor cells, but the vast majority of these biomarkers have not progressed beyond initial research discovery, and none have yet been approved for clinical use in early stage disease. Here, the authors review the crucial considerations of developing pipelines for the rapid evaluation of circulating biomarkers for breast cancer.

Serum antibody signature directed against Candida albicans Hsp90 and enolase detects invasive candidiasis in non-neutropenic patients

Invasive candidiasis (IC) adds significantly to the morbidity and mortality of non-neutropenic patients if not diagnosed and treated early. To uncover serologic biomarkers that alone or in combination could reliably detect IC in this population, IgG antibody-reactivity profiles to the Candida albicans intracellular proteome were examined by serological proteome analysis (SERPA) and data mining procedures in a training set of 24 non-neutropenic patients. Despite the high interindividual molecular heterogeneity, unsupervised clustering analyses revealed that serum 22-IgG antibody-reactivity patterns differentiated IC from non-IC patients. Univariate analyses further highlighted that 15 out of the 22 SERPA-identified IgG antibodies could be useful candidate IC biomarkers. The diagnostic performance of one of these candidates (anti-Hsp90 IgG antibodies) was validated using an ELISA prototype in a test set of 59 non-neutropenic patients. We then formulated an IC discriminator based on the combined immunoproteomic fingerprints of this and another SERPA-detected and previously validated IC biomarker (anti-Eno1 IgG antibodies) in the training set. Its consistency was substantiated using their ELISA prototypes in the test set. Receiver-operating-characteristic curve analyses showed that this two-biomarker signature accurately identified IC in non-neutropenic patients and provided better IC diagnostic accuracy than the individual biomarkers alone. We conclude that this serum IgG antibody signature directed against C. albicans Hsp90 and Eno1, if confirmed prospectively, may be useful for IC diagnosis in non-neutropenic patients.

Analysis of the differences of serum protein mass spectrometry in patients with triple negative breast cancer and non-triple negative breast cancer

The objective of the present study was to investigate differences of serum protein mass spectrometry in patients with triple negative breast cancer (TNBC) and non-TNBC and thus to search for candidate serum protein biomarkers for identification and diagnosis of TNBC. Thirty serum samples from patients with TNBC without any treatment and 30 serum samples from patients with non-TNBC without any treatment were detected by using two-dimensional gel electrophoresis and matrix-assisted laser dissociation tandem time-of-flight mass spectrometry (MALDI-TOF-MS). PDQest 7.0 software of Bio-Rad was adopted to screen differentially expressed proteins. Protein ID retrieval was conducted by using Mascot software to confirm the results of differential proteins. Two-dimensional gel electrophoresis profiles were obtained successfully. A total of 16 differential protein loci were discovered by analyzing patient sera of the two groups using two-dimensional gel electrophoresis analysis software. Ten differential proteins were identified by mass spectrometric analysis in the 16 differential proteins. Combined with database and literature search results, it is speculated that the specifically upregulated proteins and downregulated proteins including transthyretin, haptoglobin, and antitrypsin may be the potential markers for early diagnosis of TNBC. Comparing the TNBC patients with the non-TNBC patients, there are differences in serum protein compositions. The ten differential proteins discovered in the present study provide reference basis for further improving early diagnosis and identification and diagnosis index of TNBC. Especially, transthyretin, haptoglobin, and antitrypsin show dramatic significances for the early diagnosis of TNBC.

A multiparametric serum marker panel as a complementary test to mammography for the diagnosis of node-negative early-stage breast cancer and DCIS in young women

BACKGROUND

The sensitivity of mammography for the detection of small lesions, including node-negative early-stage (T1N0) primary breast cancer (PBC) and ductal carcinoma in situ (DCIS), is significantly decreased in young patients. From a clinical standpoint, an inconclusive mammogram reflects the inability of clinicians to confidently decide whether patients should be referred for biopsy or for follow-up with repeat imaging.

METHODS

Specific ELISAs were developed for a panel of 13 well-recognized breast autoantigens (HSP60, FKBP52, PRDX2, PPIA, MUC1, GAL3, PAK2, P53, CCNB1, PHB2, RACK1, RUVBL1, and HER2). Circulating autoantibody levels were measured in a cohort of 396 serum samples from histologically confirmed DCIS (n = 87) or T1N0 PBC (n = 153) and healthy controls (n = 156).

RESULTS

Individually, antibodies against CCNB1, FKBP52, GAL3, PAK2, PRDX2, PPIA, P53, and MUC1 demonstrated discriminatory power between breast cancer and healthy control groups. At 90% sensitivity, the overall combined specificity of the autoantibody serum screening test was 42%. Adjustment for higher sensitivities of 95% and 99% resulted in 30% and 21% specificities, respectively (33% and 18% in T1N0 PBC and 28% and 21% in DCIS). Finally, in patients with node-negative early-stage breast cancer younger than 50 years, the autoantibody assay exhibited 59% specificity with a fixed sensitivity at 90%.

CONCLUSIONS

Our autoantibody panel allows accurate detection of early breast cancer and DCIS, notably in younger patients.

IMPACT

Clinical assessment of this autoantibody panel displays a potential to facilitate clinical management of early-stage breast cancer detection in cases of inconclusive mammogram.

MALDI-TOF MS as evolving cancer diagnostic tool: a review

Recent developments in mass spectrometry have introduced clinical proteomics to the forefront of diseases diagnosis, offering reliable, robust and efficient analytical method for biomarker discovery and monitoring. MALDI-TOF is a powerful tool for surveying proteins and peptides comprising the realm for clinical analysis. MALDI-TOF has the potential to revolutionize cancer diagnostics by facilitating biomarker discovery, enabling tissue imaging and quantifying biomarker levels. Healthy (control) and cancerous tissues can be analyzed on the basis of mass spectrometry (MALDI-TOF) imaging to identify cancer-specific changes that may prove to be clinically useful. We review MALDI-TOF profiling techniques as tools for detection of cancer biomarkers in various cancers. We mainly discuss recent advances including period from 2011 to 2013.

Tumor-associated autoantibodies as diagnostic and prognostic biomarkers

In the process of tumorigenesis, normal cells are remodeled to cancer cells and protein expression patterns are changed to those of tumor cells. A newly formed tumor microenvironment elicits the immune system and, as a result, a humoral immune response takes place. Although the tumor antigens are undetectable in sera at the early stage of tumorigenesis, the nature of an antibody amplification response to antigens makes tumor-associated autoantibodies as promising early biomarkers in cancer diagnosis. Moreover, the recent development of proteomic techniques that make neo-epitopes of tumor-associated autoantigens discovered concomitantly has opened a new area of ‘immuno-proteomics’, which presents tumor-associated autoantibody signatures and confers information to redefine the process of tumorigenesis. In this article, the strategies recently used to identify and validate serum autoantibodies are outlined and tumor-associated antigens suggested until now as diagnostic/prognostic biomarkers in various tumor types are reviewed. Also, the meaning of autoantibody signatures and their clinical utility in personalized medicine are discussed. [BMB Reports 2012; 45(12): 677-685]