Browse
Submit Data
Databases
API
Help

Dataset Information

5 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Clinical study on individualized and precise immunotherapy for colorectal cancer based on high-throughput tumor antigen polypeptides screening

ABSTRACT: Interventions: therapy group:Individualized and precise immunotherapy for colorectal cancer based on high-throughput tumor antigen polypeptides screening Primary outcome(s): Incidence of adverse events;Progression free survival Study Design: Single arm

DISEASE(S): Colorectal Cancer

PROVIDER: 2705817 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

ACCESS DATA

Json Xml

Similar Datasets

Clinical study on diagnosis of colorectal cancer based on high-throughput tumor antigen polypeptides screening

Project description:Interventions: Gold Standard:Pathological diagnosis;Index test:high-throughput tumor antigen polypeptides screening Primary outcome(s): Diagnostic accuracy Study Design: Factorial

| 2704426 | ecrin-mdr-crc

A novel medication decision gene signature predicts response to individualized therapy and prognosis outcomes in hepatocellular carcinoma patients

Project description:Molecular targeted therapy has shown potential in hepatocellular carcinoma (HCC) patients, and immunotherapy applications are developing rapidly. However, clinical guidance for making individualized therapy decisions for HCC patients remains lacking. To facilitate individualized and reasonable clinical guidance for each HCC patient, we constructed the MDH score.

2022-09-22 | GSE213615 | GEO

Establishment of Individualized Immunotherapy Strategy and Platform Based on Changes of Intestinal Microbiota

Project description:To explore and analyze the relationship between intestinal flora changes and the efficacy of individualized immunotherapy in patients with upper gastrointestinal cancer, and to find new biomarkers to predict the efficacy of immunotherapy, bringing new breakthroughs in tumor diagnosis and treatment.

| 2391273 | ecrin-mdr-crc

Antigen-Multimers: Specific, Sensitive, Precise, and Multifunctional High-Avidity CAR-Staining Reagents

Project description:Antigen-Multimers: Specific, Sensitive, Precise, and Multifunctional High-Avidity CAR-Staining Reagents

| PRJNA715188 | ENA

Tumor immunological phenotype signature-based high-throughput screening for the discovery of combination immunotherapy compounds

Project description:Immune checkpoint blockade (ICB) therapy intends to only benefit a fraction of cancer patients, and combination immunotherapy with a compound is a promising treatment to overcome this limitation. Here, a tumor immunological phenotype (TIP) gene signature and high throughput sequencing-based high throughput screening (HTS2) were combined to identify combination immunotherapy compounds. We firstly defined a TIP gene signature, which expression pattern distinguishes “cold” tumors from “hot” tumors, and predicts ICB response in cancer patients. Then, after screening thousands of compounds, we identified that aurora kinase inhibitors, including ENMD-2076 and TAK-901, could reprogram the expression pattern of TIP genes from “cold” tumor to “hot” tumor in triple negative breast cancer (TNBC) cells. The treatment of aurora kinase inhibitors on TNBC cells dramatically up-regulates expression of Th1 type chemokine genes CXCL10 and CXCL11, which promotes effective T cells infiltrating into tumor microenvironment and significantly improves anti-PD-1 efficacy in inhibiting the tumor growth of TNBC in preclinical models. Mechanistically, these aurora kinase inhibitors are mainly through inhibiting AURKA-STAT3 signaling pathway to stimulate the expression of CXCL10 and CXCL11. Our study established a high throughput strategy to discover candidate compounds for combination immunotherapy, and suggested the therapeutic potential of combining aurora kinase inhibitors with checkpoint blockade immunotherapy for the treatment of TNBC.

2020-12-31 | GSE160071 | GEO

Optimizing High-Throughput Shotgun Immunoproteomics for Antigen Identification

Project description:Identification of individual proteins (i.e., antigens) which initiate and/or perpetuate adaptive immune responses has potential to greatly impact pre-clinical and clinical work across numerous fields. To date, however, the methodologies available to identify antigens responsible for driving adaptive immune responses have been plagued by numerous issues which have drastically limited their widespread adoption. Therefore, in this study, we sought to optimize a shotgun immunoproteomics approach to alleviate these persistent issues and create a high-throughput, quantitative methodology for antigen identification. Three individual components of a previously published approach, namely the protein extraction, antigen elution, and LC-MS/MS analysis steps, were optimized in a systematic manner. These studies determined that preparation of protein extracts using a one-step tissue disruption method in immunoprecipitation (IP) buffer, eluting antigens from affinity chromatography columns with 1% trifluoroacetic acid (TFA), and TMT-labeling & multiplexing equal volumes of eluted samples for LC-MS/MS analysis, resulted in quantitative longitudinal antigen identification, with reduced variability between replicates and increased total number of antigens identified. This optimized pipeline provides a multiplexed, highly reproducible, and fully quantitative approach to antigen identification which is broadly applicable to determine the role of antigenic proteins in inciting (i.e. primary antigens) and perpetuating (i.e., secondary antigens) a wide range of diseases.

2023-04-18 | PXD038761 | Pride

RNA-seq alignment to individualized genomes

Project description:The source of most errors in RNA sequencing (RNA-seq) read alignment is in the repetitive structure of the genome and not with the alignment algorithm. Genetic variation away from the reference sequence exacerbates this problem causing reads to be assigned to the wrong location. We developed a method, implemented as the software package Seqnature, to construct the imputed genomes of individuals (individualized genomes) of experimental model organisms including inbred mouse strains and genetically unique outbred animals. Alignment to individualized genomes increases read mapping accuracy and improves transcript abundance estimates. In an application to expression QTL mapping, this approach corrected erroneous linkages and unmasked thousands of hidden associations. Individualized genomes accounting for genetic variation will be useful for human short-read sequencing and other sequencing applications including ChIP-seq.

2014-06-10 | GSE45684 | GEO

Individualized proteogenomics reveals mutational landscape of melanoma patients in response to immunotherapy

Project description:Immune checkpoint inhibitors are used to restore or augment antitumor immune response and show great promise in treatment of melanoma and other types of cancers. However, only a relatively small percentage of patients are fully responsive to immune checkpoint inhibition, mostly due to tumor heterogeneity and primary resistance to therapy. Both of these features are largely driven by accumulation of patient-specific mutations, pointing to the need for personalized approaches in diagnostics and immunotherapy. Proteogenomics integrates patient-specific genomic and proteomic data to study cancer development and resistance mechanisms, as well as tumor heterogeneity in individual patients. Here, we use a proteogenomic approach to characterize the mutational landscape of samples derived from four clinical melanoma patients at the genomic, proteomic and phosphoproteomic level. Integration of datasets enabled identification and quantification of an extensive number of sample-specific amino acid variants, among them many were not previously reported in melanoma. We detected a disproportional number of alternate peptides between treated and untreated (naïve) samples with a high potential to influence signal transduction. This is one of the first proteogenomic study designed to study the mutational landscape of patient-derived melanoma tissue samples in response to immunotherapy.

2022-02-16 | PXD028700 | Pride

High-throughput profiling of antigen-specific antibody secreting cells using an antibody secretion trap (TRAPnSeq)

Project description:Following activation by cognate antigen, B cells undergo fine-tuning of their antigen receptors and may ultimately differentiate into antibody-secreting cells (ASCs). While antigen-specific antibodies from B cell receptor (BCR) expressing B cells can be readily cloned and sequenced following flow sorting, antigen-specific plasma cells that lack surface BCR cannot be easily profiled in a high-throughput way. Here, we report an approach, TRAPnSeq (antigen specificity mapping through Ig secretionTRAPandSequencing), that allows capture of secreted antibodies on the surface of ASCs, which in turn enables high-throughput screening of single ASCs against large antigen panels and recovery of paired VH:VL antibody sequences. This approach incorporates flow cytometry, standard microfluidic platforms and DNA barcoding technologies to isolate and characterize antigen-specific ASCs through single cell V(D)J, RNA and antigen barcode sequencing. We show the utility of TRAPnSeq by profiling antigen-specific IgG and IgE plasma cells from mouse and humans and validate antigen binding by ELISA. TRAPnSeq can easily be combined with existing B cell platforms to accelerate antibody discovery from ASCs and can further be expanded to any protein secreting-cells.

2023-07-07 | GSE233507 | GEO

Identification of a predictive gene signature to recMAGE A3 antigen-specific cancer immunotherapy in metastatic melanoma and non-small-cell lung cancer

Project description:Purpose: To evaluate the presence of a gene expression signature present before treatment as predictive of response to treatment with MAGEâA3 immunotherapeutic in metastatic melanoma patients and to validate its predictivity in adjuvant therapy of early-stage lung cancer. Patients were participants in two PhaseÂ II studies of the recombinant MAGEâA3 antigen combined with immunological adjuvants. mRNA from tumor samples (biopsies) collected before MAGE-A3 immunotherapy was analyzed by microarray hybridization and by quantitative polymerase chain reaction (qRT-PCR). The melanoma microarray dataset was used to discover and crossvalidate a gene expression signature and classifier discriminative of Responders (R) versus Non-Responders (NR) patients; the gene signature and classifier were then applied to an adjuvant lung cancer study. Patients that were not included for analysis are denoted as NE (Non-evaluable). GSK Biologicals

2013-05-30 | E-GEOD-35640 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data