Dataset Information

Serum autoantibody profiling using a natural glycoprotein microarray for the prognosis of early melanoma.

ABSTRACT: The poor prognosis of melanoma and the high cost of lymph node biopsy for melanoma patients have led to an urgent need for the discovery of convenient and accurate prognostic indicators. Here, we have developed a natural glycoprotein microarray to discover serum autoantibodies to distinguish between patients with node negative melanoma and node positive melanoma. Dual-lectin affinity chromatography was used to extract glycoproteins from a melanoma cell line. Liquid-based reverse phase separation and microarray platforms were then applied to separate and spot these natural proteins on nitrocellulose slides. The serum autoantibodies were investigated by exposing these proteins to sera from 43 patients that have already been diagnosed to have different stages of early melanoma. The combination of 9 fractions provides a 55% sensitivity with 100% specificity for the detection of node positive against node negative and a 62% sensitivity with 100% specificity for the detection of node negative against node positive. Recombinant proteins were used to confirm the results using a sample set with 79 patients with diagnosed melanoma. The response of sera against recombinant 94 kD glucose-regulated protein (GRP94), acid ceramidase (ASAH1), cathepsin D (CTSD), and lactate dehydrogenase B (LDHB) shared a similar pattern to the fractions where they were identified. The glycoarray platform provides a convenient and highly reproducible method to profile autoantibodies that could be used as serum biomarkers for prognosis of melanoma.

SUBMITTER: Liu Y

PROVIDER: S-EPMC2974814 | biostudies-literature | 2010 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Serum autoantibody profiling using a natural glycoprotein microarray for the prognosis of early melanoma.

Liu Yashu Y He Jintang J Xie Xaiolei X Su Gang G Teitz-Tennenbaum Seagal S Sabel Michael S MS Lubman David M DM

Journal of proteome research 20101020 11

The poor prognosis of melanoma and the high cost of lymph node biopsy for melanoma patients have led to an urgent need for the discovery of convenient and accurate prognostic indicators. Here, we have developed a natural glycoprotein microarray to discover serum autoantibodies to distinguish between patients with node negative melanoma and node positive melanoma. Dual-lectin affinity chromatography was used to extract glycoproteins from a melanoma cell line. Liquid-based reverse phase separation ...[more]

PMID: 20879797

Similar Datasets

Project description:Tumor stage predicts pancreatic cancer (PDAC) prognosis, but prolonged and short survivals have been described in patients with early-stage tumors. Circulating microRNA (miRNA) are an emerging class of suitable biomarkers for PDAC prognosis. Our aim was to identify whether serum miRNA signatures predict survival of early-stage PDAC. Serum RNA from archival 15 stage I-III PDAC patients and 4 controls was used for miRNAs expression profile (Agilent microarrays). PDAC patients with comparable age, gender, diabetes, jaundice and surgery were classified according to survival: less than 14 months (7/15 pts, group A) and more than 22 months (8/15 pts, group B). Bioinformatic data analysis was performed by two-class Significance Analysis of Microarray (SAM) algorithm. Binary logistic regression analyses considering PDAC diagnosis and outcome as dependent variables, and ROC analyses were also performed. 2549 human miRNAs were screened out. At SAM, 76 differentially expressed miRNAs were found among controls and PDAC (FDR = 0.4%), the large majority (50/76, 66%) of them being downregulated in PDAC with respect to controls. Six miRNAs were independently correlated with early PDAC, and among these, hsa-miR-6821-5p was associated with the best ROC curve area in distinguishing controls from early PDAC. Among the 71 miRNAs differentially expressed between groups A and B, the most significant were hsa-miR-3135b expressed in group A only, hsa-miR-6126 and hsa-miR-486-5p expressed in group B only. Eight miRNAs were correlated with the presence of lymph-node metastases; among these, hsa-miR-4669 is of potential interest. hsa-miR-4516, increased in PDAC and found as an independent predictor of survival, has among its putative targets a series of gens involved in key pathways of cancer progression and dissemination, such as Wnt and p53 signalling pathways. A series of serum miRNAs was identified as potentially useful for the early diagnosis of PDAC, and for establishing a prognosis.

Project description:Although multiple serum antiretinal autoantibodies (ARAs) have been reported in patients with paraneoplastic and non-paraneoplastic autoimmune retinopathy ((n)pAIR), not all retinal antigens involved in (n)pAIR are specified. This study aims to serologically identify patients with presumed (n)pAIR through determination of both known and unknown ARAs by autoantibody profiling.An antigen suspension bead array using 188 different antigens representing 97 ocular proteins was performed to detect ARAs in serum samples of patients with presumed (n)pAIR (n = 24), uveitis (n = 151) and cataract (n = 21). Logistic regressions were used to estimate the associations between ocular antigens and diagnosis. Validation of interphotoreceptor matrix proteoglycan 2 (IMPG2) and recoverin antigens was performed by immunohistochemistry and immunoblot, respectively.Samples of patients with presumed (n)pAIR exhibited a broad spectrum of ARAs. We identified retinal antigens that have already been described previously (e.g. recoverin), but also identified novel ARA targets. Most ARAs were not specific for (n)pAIR since their presence was also observed in patients with cataract or uveitis. High titers of autoantibodies directed against photoreceptor-specific nuclear receptor and retinol-binding protein 3 were more common in patients with presumed (n)pAIR compared to uveitis (p = 0.015 and p = 0.018, respectively). The presence of all other ARAs did not significantly differ between groups. In patients with presumed (n)pAIR, anti-recoverin autoantibodies were the most prevalent ARAs. Validation of bead array results by immunohistochemistry (anti-IMPG2) and immunoblot (anti-recoverin) showed concordant results in (n)pAIR patients.Patients with (n)pAIR are characterized by the presence of a broad spectrum of ARAs. The diagnosis of (n)pAIR cannot be based on the mere presence of serum ARAs, as these are also commonly present in uveitis as well as in age-related cataract patients.

Project description:BackgroundAutoantibodies against tumor associated antigens are highly related to cancer progression. Autoantibodies could serve as indicators of tumor burden, and have the potential to monitor the response of treatment and tumor recurrence. However, how the autoantibody repertoire changes in response to cancer treatment are largely unknown.MethodsSera of five lung adenocarcinoma patients before and after surgery, were collected longitudinally. These sera were analyzed on a human proteome microarray of 20,240 recombinant proteins to acquire dynamic autoantibody repertoire in response to surgery, as well as to identify the antigens with decreased antibody response after tumor excision or surgery, named as surgery-associated antigens. The identified candidate antigens were then used to construct focused microarray and validated by longitudinal sera collected from a variety of time points of the same patient and a larger cohort of 45 sera from lung adenocarcinoma patients.FindingsThe autoantibody profiles are highly variable among patients. Meanwhile, the autoantibody profiles of the sera from the same patient were surprisingly stable for at least 3 months after surgery. Six surgery-associated antigens were identified and validated. All the five patients have at least one surgery-associated antigen, demonstrating this type of biomarkers is prevalent, while specific antigens are poorly shared among individuals. The prevalence of each antigen is 2%-14% according to the test with a larger cohort.InterpretationTo our knowledge, this is the first study of dynamically profiling of autoantibody repertoires before/after surgery of cancer patients. The high prevalence of surgery-associated antigens implies the possible broad application for monitoring of tumor recurrence in population, while the low prevalence of specific antigens allows personalized medicine. After the accumulation and analysis of more longitudinal samples, the surgery-associated serum biomarkers, combined as a panel, may be applied to alarm the recurrence of tumor in a personalized manner.FundingResearch supported by grants from National Key Research and Development Program of China Grant (No. 2016YFA0500600), National Natural Science Foundation of China (No. 31970130, 31600672, 31670831, and 31370813), Open Foundation of Key Laboratory of Systems Biomedicine (No. KLSB2017QN-01), Science and Technology Commission of Shanghai Municipality Medical Guidance Science &Technology Support Project (16411966100), Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support (20172005), Shanghai Municipal Commission of Health and Family Planning Outstanding Academic Leaders Training Program (2017BR055) and National Natural Science Foundation of China (81871882).

Project description:Background: Tumor stage predicts pancreatic cancer (PDAC) prognosis, but prolonged and short survivals have been described in patients with early-stage tumors. Circulating microRNA (miRNA) are an emerging class of suitable biomarkers for PDAC prognosis. Our aim was to identify whether serum miRNA signatures predict survival of early-stage PDAC. Methods: Se-rum RNA from archival 15 stage I-III PDAC patients and 4 controls was used for miRNAs ex-pression profile (Agilent microarrays). PDAC patients with comparable age, gender, diabetes, jaundice and surgery were classified according to survival: less than 14 months (7/15 pts, group A) and more than 22 months (8/15 pts, group B). Bioinformatic data analysis was performed by two-class Significance Analysis of Microarray (SAM) algorithm. Binary logistic regression analyses considering PDAC diagnosis and outcome as dependent variables, and ROC analyses were also performed. Results: 2549 human miRNAs were screened out. At SAM, 76 differen-tially expressed miRNAs were found among controls and PDAC (FDR = 0.4%), the large major-ity (50/76, 66%) of them being downregulated in PDAC with respect to controls. Six miRNAs were independently correlated with early PDAC, and among these, hsa-miR-6821-5p was asso-ciated with the best ROC curve area in distinguishing controls from early PDAC. Among the 71 miRNAs differentially expressed between groups A and B, the most significant were hsa-miR-3135b expressed in group A only, hsa-miR-6126 and hsa-miR-486-5p expressed in group B only. Eight miRNAs were correlated with the presence of lymph-node metastases; among these, hsa-miR-4669 is of potential interest. hsa-miR-4516, increased in PDAC and found as an independent predictor of survival, has among its putative targets a series of gens involved in key pathways of cancer progression and dissemination, such as Wnt and p53 signaling pathways. Conclusions: A series of serum miRNAs was identified as potentially useful for the early diag-nosis of PDAC, and for establishing a prognosis

Dataset Information

Serum autoantibody profiling using a natural glycoprotein microarray for the prognosis of early melanoma.

Publications

Serum autoantibody profiling using a natural glycoprotein microarray for the prognosis of early melanoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets