ID
45605
Description
Principal Investigator: Hanlee Ji, MD, Stanford University School of Medicine, Palo Alto, USA MeSH: Lymphoma, Follicular,Lymphoma, Non-Hodgkin https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001378 Follicular lymphoma (FL) is a generally incurable B-cell malignancy which has the potential to transform into highly aggressive lymphomas. Genomic studies indicate it is often a small subpopulation rather than the dominant population in the FL that gives rise to the more aggressive subtype. To resolve the underlying transcriptional networks of follicular B-cell lymphomas at single molecule and cell resolution, we leveraged droplet-based barcoding technology for highly parallel single cell RNA-Seq. We analyzed the transcriptomes from tens of thousands of cells derived from five primary FL tumors. Simultaneously, we conducted multi-dimensional flow cell sorting to validate our characterizing of cellular lineages and critical expressed proteins. For each tumor, we identified multiple cellular subpopulations, matching known hematopoietic lineages. Comparison of gene expression by matched malignant and normal B cells from the same patient revealed tumor-specific features. Malignant B cells exhibited restricted immunoglobulin light chain expression (either Ig Kappa or Ig Lambda), as well the expected upregulation of the BCL2 gene, but also down-regulation of the FCER2, CD52 and MHC class II genes. By leveraging the single-cell resolution on large numbers of cells per patient, we were able to examine tumor-resident T cells. We identified pairs of immune checkpoint molecules that were co-expressed, providing a potentially useful strategy for selection of patient-tailored combination immunotherapies. In summary, massively parallel measurement of single-cell expression in thousands of tumor cells and tumor-resident lymphocytes can be used to obtain a systems-level view of the tumor microenvironment and identify new avenues for therapeutic development.
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Versions (1)
- 19/02/2023 19/02/2023 - Chiara Middel
Détendeur de droits
Hanlee Ji, MD, Stanford University School of Medicine, Palo Alto, USA
Téléchargé le
19 février 2023
DOI
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Licence
Creative Commons BY 4.0
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dbGaP phs001378 scRNA-Seq Reveals Lymphoma B Cell Diversity and T Cell Immune Checkpoint Co-Expression
This subject phenotype table contains subject ID, age onset, sex, race, and age.
- StudyEvent: SEV1
- Eligibility Criteria
- The subject consent file includes subject IDs, consent information, subject source, and affection status of the subject for Follicular Lymphoma.
- This data table contains a mapping of study subject IDs to sample IDs. Samples are the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs. The data table also includes sample source and sample use.
- This subject phenotype table contains subject ID, age onset, sex, race, and age.
- This sample attributes table contains sample ID, body site, analyte type, tumor status, histological type, tumor or transformed cell line, tumor stage, tumor grade, and tumor treatment.
Similar models
This subject phenotype table contains subject ID, age onset, sex, race, and age.
- StudyEvent: SEV1
- Eligibility Criteria
- The subject consent file includes subject IDs, consent information, subject source, and affection status of the subject for Follicular Lymphoma.
- This data table contains a mapping of study subject IDs to sample IDs. Samples are the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs. The data table also includes sample source and sample use.
- This subject phenotype table contains subject ID, age onset, sex, race, and age.
- This sample attributes table contains sample ID, body site, analyte type, tumor status, histological type, tumor or transformed cell line, tumor stage, tumor grade, and tumor treatment.
C2348585 (UMLS CUI [1,2])