Nucleic Acid Programmable Protein Arrays (NAPPA) Somatic p53 Mutations
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE77949 | GEO | 2016/06/01
SECONDARY ACCESSION(S): PRJNA312188
REPOSITORIES: GEO
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Project description:Purpose: Mutations in TP53 induce autoantibody immune responses in a subset of cancer patients, which have been proposed as biomarkers for early detection. Here, we investigate the association of p53 specific autoantibodies with multiple tumor subtypes and determine the association with p53 mutation status and epitope specificity. Experimental Design: IgG p53 autoantibodies (p53-AAb), were quantified in 412 serum saples using a programmable ELISA assay from patients with serous ovarian, pancreatic adenocarcinoma, and breast cancer. To determine if patients generated mutation specific autoantibodies we designed a panel of the most relevant 51 p53 point mutant proteins, to be displayed on custom programmable protein microarrays. To determine the epitope specificity we displayed 12 overlapping tiling fragments and 38 N- and C-terminal deletions spanning the length of the wild-type p53 proteins. Results: We detected p53-AAb with sensitivities of 58.8% (ovarian), 22% (pancreatic), 32% (triple negative breast cancer), and 10.2% (HER2+ breast cancer) at 94% specificity. Sera with p53-AAb contained broadly-reactive autoantibodies to 51 displayed p53 mutant proteins, demonstrating a polyclonal response to common epitopes. All p53-AAb displayed broad polyclonal immune response to both continuous and discontinuous epitopes at the N- and C-terminus as well as the DNA binding domain. Conclusion and clinical relevance: In this comprehensive analysis, mutations in tumor p53 induce strong, polyclonal autoantibodies with broadly reactive epitope specificity. The immunoreactivity was compared between 60 pancreactic ductal adenocarcinoma cases and 63 benign pancreatic disease controls against 52 unique mutant p53 and 379 human proteins that were printed on microscope slides. [Contributor] Arizona State University
2016-06-01 | E-GEOD-77949 | biostudies-arrayexpress
Project description:Introduction: Serous ovarian cancer is the leading cause of gynecological cancers, with a 5-year survival rate below 45% due in part to the nonspecific symptoms and lack of accurate screening for early detection. In comparison, patients diagnosed at an early stage have a five-year survival rate of 92%, demonstrating the urgent need for biomarkers for the early detection of disease. Serum from patients with serous ovarian cancer contain antibodies to tumor antigens that are potential biomarkers for early detection. The purpose of this study is to identify a panel of novel serum autoantibody (AAb) biomarkers for the early diagnosis of serous ovarian cancer. Methods: To detect AAb we probed high-density programmable protein microarrays (NAPPA) containing 10,247 antigens with sera from patients with serous ovarian cancer (n = 30 cases/ 30 healthy controls) and measured bound IgG. We identified 735 promising tumor antigens using cutoff values of 10% sensitivity at 95% specificity and K-value>0.8, as well as visual analysis and evaluated these with an independent set of serous ovarian cancer sera (n = 30 cases/ 30 benign disease controls/ 30 heathy controls). Thirty-nine potential tumor autoantigens were identified with sensitivities ranging from 3 to 39.7% sensitivity at 95% specificity and were retested using an orthogonal programmable ELISA assay. A total of 13 potential tumor antigens were identified for further validation using an independent ovarian cancer sera set (n = 44 cases/ 34 healthy controls). Sensitivities at 95% specificity were calculated and a serous ovarian cancer classifier was constructed. In addition, we evaluated a longitudinal study using blinded serous pre-diagnostic ovarian cancer sera (n = 9 cases/ 90 controls) to examine the value of three (CTAG1, CTAG2, and p53) of these AAb in comparison to CA 125. Results: We identified 11-AAbs (ICAM3, CTAG2, p53, STYXL1, PVR, POMC, NUDT11, TRIM39, UHMK1, KSR1, and NXF3) that distinguished serous ovarian cancer cases from healthy controls with a combined 45% sensitivity at 100% specificity. In our longitudinal analysis, p53- and CTAG-AAb were detected up to 9 months prior to ovarian cancer diagnosis and increased with CA 125 levels. Conclusion: These are potential circulating biomarkers for the early detection of serous ovarian cancer, and warrant confirmation in larger clinical cohorts. In addition, p53- and CTAG1/2-AAb are detected in a subset of women with ovarian cancer up to 9 months prior to clinical diagnosis. Their utility as a biomarker for early detection, beyond CA 125, warrant further investigation.
2017-06-01 | GSE79516 | GEO
Project description:Introduction: Serous ovarian cancer is the leading cause of gynecological cancers, with a 5-year survival rate below 45% due in part to the nonspecific symptoms and lack of accurate screening for early detection. In comparison, patients diagnosed at an early stage have a five-year survival rate of 92%, demonstrating the urgent need for biomarkers for the early detection of disease. Serum from patients with serous ovarian cancer contain antibodies to tumor antigens that are potential biomarkers for early detection. The purpose of this study is to identify a panel of novel serum autoantibody (AAb) biomarkers for the early diagnosis of serous ovarian cancer. Methods: To detect AAb we probed high-density programmable protein microarrays (NAPPA) containing 10,247 antigens with sera from patients with serous ovarian cancer (n = 30 cases/ 30 healthy controls) and measured bound IgG. We identified 735 promising tumor antigens using cutoff values of 10% sensitivity at 95% specificity and K-value>0.8, as well as visual analysis and evaluated these with an independent set of serous ovarian cancer sera (n = 30 cases/ 30 benign disease controls/ 30 heathy controls). Thirty-nine potential tumor autoantigens were identified with sensitivities ranging from 3 to 39.7% sensitivity at 95% specificity and were retested using an orthogonal programmable ELISA assay. A total of 13 potential tumor antigens were identified for further validation using an independent ovarian cancer sera set (n = 44 cases/ 34 healthy controls). Sensitivities at 95% specificity were calculated and a serous ovarian cancer classifier was constructed. In addition, we evaluated a longitudinal study using blinded serous pre-diagnostic ovarian cancer sera (n = 9 cases/ 90 controls) to examine the value of three (CTAG1, CTAG2, and p53) of these AAb in comparison to CA 125. Results: We identified 11-AAbs (ICAM3, CTAG2, p53, STYXL1, PVR, POMC, NUDT11, TRIM39, UHMK1, KSR1, and NXF3) that distinguished serous ovarian cancer cases from healthy controls with a combined 45% sensitivity at 100% specificity. In our longitudinal analysis, p53- and CTAG-AAb were detected up to 9 months prior to ovarian cancer diagnosis and increased with CA 125 levels. Conclusion: These are potential circulating biomarkers for the early detection of serous ovarian cancer, and warrant confirmation in larger clinical cohorts. In addition, p53- and CTAG1/2-AAb are detected in a subset of women with ovarian cancer up to 9 months prior to clinical diagnosis. Their utility as a biomarker for early detection, beyond CA 125, warrant further investigation.
2017-06-01 | GSE79498 | GEO
Project description:Introduction: Serous ovarian cancer is the leading cause of gynecological cancers, with a 5-year survival rate below 45% due in part to the nonspecific symptoms and lack of accurate screening for early detection. In comparison, patients diagnosed at an early stage have a five-year survival rate of 92%, demonstrating the urgent need for biomarkers for the early detection of disease. Serum from patients with serous ovarian cancer contain antibodies to tumor antigens that are potential biomarkers for early detection. The purpose of this study is to identify a panel of novel serum autoantibody (AAb) biomarkers for the early diagnosis of serous ovarian cancer. Methods: To detect AAb we probed high-density programmable protein microarrays (NAPPA) containing 10,247 antigens with sera from patients with serous ovarian cancer (n = 30 cases/ 30 healthy controls) and measured bound IgG. We identified 735 promising tumor antigens using cutoff values of 10% sensitivity at 95% specificity and K-value>0.8, as well as visual analysis and evaluated these with an independent set of serous ovarian cancer sera (n = 30 cases/ 30 benign disease controls/ 30 heathy controls). Thirty-nine potential tumor autoantigens were identified with sensitivities ranging from 3 to 39.7% sensitivity at 95% specificity and were retested using an orthogonal programmable ELISA assay. A total of 13 potential tumor antigens were identified for further validation using an independent ovarian cancer sera set (n = 44 cases/ 34 healthy controls). Sensitivities at 95% specificity were calculated and a serous ovarian cancer classifier was constructed. In addition, we evaluated a longitudinal study using blinded serous pre-diagnostic ovarian cancer sera (n = 9 cases/ 90 controls) to examine the value of three (CTAG1, CTAG2, and p53) of these AAb in comparison to CA 125. Results: We identified 11-AAbs (ICAM3, CTAG2, p53, STYXL1, PVR, POMC, NUDT11, TRIM39, UHMK1, KSR1, and NXF3) that distinguished serous ovarian cancer cases from healthy controls with a combined 45% sensitivity at 100% specificity. In our longitudinal analysis, p53- and CTAG-AAb were detected up to 9 months prior to ovarian cancer diagnosis and increased with CA 125 levels. Conclusion: These are potential circulating biomarkers for the early detection of serous ovarian cancer, and warrant confirmation in larger clinical cohorts. In addition, p53- and CTAG1/2-AAb are detected in a subset of women with ovarian cancer up to 9 months prior to clinical diagnosis. Their utility as a biomarker for early detection, beyond CA 125, warrant further investigation.
2017-06-01 | GSE79517 | GEO
Project description:A progressive increase in the breadth and specificity of autoantibodies over time, termed epitope spreading, drives pathogenic targeting of an ever-widening repertoire of self-components in many autoimmune diseases. Ostensibly, this progressive inclusion of additional B cell clones into an ongoing autoreactive response can occur through linked recognition, whereby proto-autoreactive B cells recognize distinct antigenic epitopes, which carry shared T cell epitopes. In a murine model displaying epitope spreading resembling that observed in systemic lupus erythematosus, we find that the epitope spreading process is compartmentalized by MHC. Antigen presentation by B cells carrying two MHC haplotypes can bridge the MHC barrier between two compartments of B cells that do not share MHC haplotypes, by communicating with two separate pools of MHC-restricted T cells. This leads to inclusion of distinct and diverse B cell reactivities in germinal centers. Our findings demonstrate a formidable capacity of B cells to drive the autoreactive response.
2022-07-01 | GSE202358 | GEO
Project description:A number of seven proteins were selected during immunoscreening and further analyses. The proteins were in silico divided into overlapping 15-mer oligopeptides with an overlap of 11 residues. The microarrays were incubated with different antibodies to C. jejuni, Escherichia coli and Salmonella enterica. Each microarray was separated into three individual incubation chambers using ProPlate 3-Well modules. Within each incubation chamber, each peptide was spotted in triplicate with the controls spotted nine times each. The controls included human-IgG, rabbit-IgG, mouse-IgG and myelin basal protein (MBP). Each chamber was incubated independently using different polyclonal antibodies to C. jejuni, and for specificity testing, with an antibody to E. coli or S. enterica. Thus, samples 4_1, 4_2, 5_1 and 5_2 represent epitope mapping of three proteins with C. jejuni antibodies, while 6_1, 6_2, 7_1 and 7_2 represent the data after incubation with an E. coli antibody investigating unspecific interactions of the antibody to the potential linear epitopes from C. jejuni. Finally, for four different proteins from C. jejuni, the set two indicated by S2 was performed. Here, S2_6_1, S2_7_1, S2_7_2, S2_8_1 and S2_8_2 indicate epitope mapping after incubation with antibodies to C. jejuni, while the remaining samples were performed to test these latter 4 proteins for specificity by incubation with antibody to S. enterica.
2013-04-06 | E-GEOD-45542 | biostudies-arrayexpress
Project description:Sanjuan2013 - Evolution of HIV T-cell epitope, control model
Control model in which the virus targets a nonimmune cell type C (e.g., hepatocytes, epithelial cells, etc.), instead of T H
cells.
This model is described in the article:
Immune activation promotes evolutionary conservation of T-cell epitopes in HIV-1.
Sanjuán R, Nebot MR, Peris JB, Alcamí J.
PLoS Biol. 2013 Apr;11(4):e1001523
Abstract:
The immune system should constitute a strong selective pressure promoting viral genetic diversity and evolution. However, HIV shows lower sequence variability at T-cell epitopes than elsewhere in the genome, in contrast with other human RNA viruses. Here, we propose that epitope conservation is a consequence of the particular interactions established between HIV and the immune system. On one hand, epitope recognition triggers an anti-HIV response mediated by cytotoxic T-lymphocytes (CTLs), but on the other hand, activation of CD4(+) helper T lymphocytes (TH cells) promotes HIV replication. Mathematical modeling of these opposite selective forces revealed that selection at the intrapatient level can promote either T-cell epitope conservation or escape. We predict greater conservation for epitopes contributing significantly to total immune activation levels (immunodominance), and when TH cell infection is concomitant to epitope recognition (trans-infection). We suggest that HIV-driven immune activation in the lymph nodes during the chronic stage of the disease may offer a favorable scenario for epitope conservation. Our results also support the view that some pathogens draw benefits from the immune response and suggest that vaccination strategies based on conserved TH epitopes may be counterproductive.
This model is hosted on BioModels Database
and identified
by: MODEL1302180002
.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource
for published quantitative kinetic models
.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain
Dedication
for more information.
2005-01-01 | MODEL1302180002 | BioModels
Project description:Antigen-antibody interactions play a key role in the immune response post vaccination and the mechanism of action of antibody-based biopharmaceuticals. 4CMenB is a multicomponent vaccine against Neisseria meningitidis serogroup B in which factor H binding protein (fHbp) is one of the key antigens. In this study, we use hydrogen/deuterium exchange mass spectrometry (HDX-MS) to identify epitopes in fHbp recognized by polyclonal antibodies (pAb) from two human donors (HDs) vaccinated with 4CMenB. Our HDX-MS data reveal several epitopes recognized by the complex mixture of human pAb. Furthermore, we show that the pAb from the two HDs recognize the same epitope regions. Epitope mapping of total pAb and purified fHbp-specific pAb from the same HD reveals that the two antibody samples recognize the same main epitopes, showing that HDX-MS based epitope mapping can, in this case at least, be performed directly using total IgG pAb samples that have not undergone Ab-selective purification. Two monoclonal antibodies (mAb) were previously produced from B-cell repertoire sequences from one of the HDs and used for epitope mapping of fHbp with HDX-MS. The epitopes identified for the pAb from the same HD in this study, overlap with the epitopes recognized by the two individual mAbs. Overall, HDX-MS epitope mapping appears highly suitable for simultaneous identification of epitopes recognized by pAb from human donors and to thus both guide vaccine development and study basic human immunity to pathogens, including viruses.
2024-05-24 | PXD046572 | Pride
Project description:Antigen-antibody interactions play a key role in the immune response post vaccination and the mechanism of action of antibody-based biopharmaceuticals. 4CMenB is a multicomponent vaccine against Neisseria meningitidis serogroup B in which factor H binding protein (fHbp) is one of the key antigens. In this study, we use hydrogen/deuterium exchange mass spectrometry (HDX-MS) to identify epitopes in fHbp recognized by polyclonal antibodies (pAb) from two human donors (HDs) vaccinated with 4CMenB. Our HDX-MS data reveal several epitopes recognized by the complex mixture of human pAb. Furthermore, we show that the pAb from the two HDs recognize the same epitope regions. Epitope mapping of total pAb and purified fHbp-specific pAb from the same HD reveals that the two antibody samples recognize the same main epitopes, showing that HDX-MS based epitope mapping can, in this case at least, be performed directly using total IgG pAb samples that have not undergone Ab-selective purification. Two monoclonal antibodies (mAb) were previously produced from B-cell repertoire sequences from one of the HDs and used for epitope mapping of fHbp with HDX-MS. The epitopes identified for the pAb from the same HD in this study, overlap with the epitopes recognized by the two individual mAbs. Overall, HDX-MS epitope mapping appears highly suitable for simultaneous identification of epitopes recognized by pAb from human donors and to thus both guide vaccine development and study basic human immunity to pathogens, including viruses.
2024-05-22 | PXD047712 | Pride
Project description:Sanjuan2013 - Evolution of HIV T-cell epitope, immune activation model
Model of cellular immune response against HIV.
This model is described in the article:
Immune activation promotes evolutionary conservation of T-cell epitopes in HIV-1.
Sanjuán R, Nebot MR, Peris JB, Alcamí J.
PLoS Biol. 2013 Apr;11(4):e1001523
Abstract:
The immune system should constitute a strong selective pressure promoting viral genetic diversity and evolution. However, HIV shows lower sequence variability at T-cell epitopes than elsewhere in the genome, in contrast with other human RNA viruses. Here, we propose that epitope conservation is a consequence of the particular interactions established between HIV and the immune system. On one hand, epitope recognition triggers an anti-HIV response mediated by cytotoxic T-lymphocytes (CTLs), but on the other hand, activation of CD4(+) helper T lymphocytes (TH cells) promotes HIV replication. Mathematical modeling of these opposite selective forces revealed that selection at the intrapatient level can promote either T-cell epitope conservation or escape. We predict greater conservation for epitopes contributing significantly to total immune activation levels (immunodominance), and when TH cell infection is concomitant to epitope recognition (trans-infection). We suggest that HIV-driven immune activation in the lymph nodes during the chronic stage of the disease may offer a favorable scenario for epitope conservation. Our results also support the view that some pathogens draw benefits from the immune response and suggest that vaccination strategies based on conserved TH epitopes may be counterproductive.
Note from the author:
this version of the model is more general that the one described in the paper. This is because: (i) it can consider simultaneously Th-epitope escape mutants, CTL-epitope escape mutants and full T-cell (Th and CTL) escape mutants, by setting the mutation rate of Th and CTL escape mutants to zero. (ii) It allows for back mutations, which were ignored in all the simulations shown in the paper. (iii) It allows for a fitness cost of escape mutants, which was set to zero in the article. (iv) pAPCs can be infected and produce viruses (the rate of viral production for pAPCs was set to zero in the paper).
This model is hosted on BioModels Database
and identified
by: MODEL1302180001
.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource
for published quantitative kinetic models
.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to the public
domain worldwide. Please refer to CC0 Public Domain
Dedication
for more information.
2005-01-01 | MODEL1302180001 | BioModels