Project description:Kidney fibrosis represents an urgent unmet clinical need due to the lack of effective therapies and inadequate understanding of the molecular pathogenesis. We have generated a comprehensive and integrated multi-omics data set (proteomics, mRNA and small RNA transcriptomics) of fibrotic kidneys that is searchable through a user-friendly web application. Two commonly used mouse models were utilized: a reversible chemical-induced injury model (folic acid (FA) induced nephropathy) and an irreversible surgically-induced fibrosis model (unilateral ureteral obstruction (UUO)). mRNA and small RNA sequencing as well as 10-plex tandem mass tag (TMT) proteomics were performed with kidney samples from different time points over the course of fibrosis development. The bioinformatics workflow used to process, technically validate, and integrate the single data sets will be described. In summary, we present temporal and integrated multi-omics data from fibrotic mouse kidneys that are accessible through an interrogation tool to provide a searchable transcriptome and proteome for kidney fibrosis researchers.
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.
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.
Project description:Purpose: This study uses a high-throughput glycan microarray to evaluate the immunological evolution of antibodies to the glyco-antigen GD2. The goal is to determine germline and affinity mature antibody specificity and affinities/ Results: Affinity mature anti-GD2 antibodies 3F8 and ch14.18 had high affinity and were highly specific for the target GD2. Germline antibodies were also hihgly specific and had surprisingly high affinity. Conclusion: Antibodies to GD2 evolved from highly specific germlines. Highly specific germlines may be critical in evading autoimmunity issues.
Project description:Purpose: This study uses a high-throughput glycan microarray to evaluate the immunological evolution of antibodies to the glyco-antigen GD2. The goal is to determine germline and affinity mature antibody specificity and affinities/ Results: Affinity mature anti-GD2 antibodies 3F8 and ch14.18 had high affinity and were highly specific for the target GD2. Germline antibodies were also hihgly specific and had surprisingly high affinity. Conclusion: Antibodies to GD2 evolved from highly specific germlines. Highly specific germlines may be critical in evading autoimmunity issues.
Project description:Purpose: This study uses a high-throughput glycan microarray to evaluate the immunological evolution of antibodies to the glyco-antigen GD2. The goal is to determine germline and affinity mature antibody specificity and affinities/ Results: Affinity mature anti-GD2 antibodies 3F8 and ch14.18 had high affinity and were highly specific for the target GD2. Germline antibodies were also hihgly specific and had surprisingly high affinity. Conclusion: Antibodies to GD2 evolved from highly specific germlines. Highly specific germlines may be critical in evading autoimmunity issues.
Project description:Protein expression profile was analyzed by antibody array for cell cycle control phosphorylation with 238 antibodies with bladder cancer cell line, TCCSUP, and KSHV-infected TCCSUP cells.
Project description:In recent years, high throughput discovery of human recombinant monoclonal antibodies (mAbs) has been applied, to greatly advance our understanding of the specificity, and functional activity of antibodies, against HIV. Thousands of antibodies have been generated and screened in functional neutralization assays, and antibodies, associated with cross-strain neutralization and passive protection in primates, have been identified. To facilitate this type of discovery, a high throughput-screening tool is needed, to accurately classify mAbs, and their antigen targets. In this study, we analyzed and evaluated a prototype microarray chip, comprised of HIV-1 recombinant proteins gp140, gp120, gp41, and several membrane proximal external region peptides. The protein microarray analysis of 11 HIV-1 envelope-specific mAbs revealed diverse binding affinities and specificities across clades. Half maximal effective concentrations, generated by our chip analysis, correlated significantly (P<0.0001) with concentrations from ELISA binding measurements. Polyclonal immune responses in plasma samples, from HIV-1 infected subjects, exhibited different binding patterns and reactivity against printed proteins. Examining the totality of the specificity of the humoral response in this way reveals the exquisite diversity, and specificity of the humoral response to HIV.