Background: Mutation of the IL2RG gene results in a form of severe combined immune deficiency (SCID-X1), which has been treated successfully with hematopoietic stem cell gene therapy. SCID-X1 gene therapy results in reconstitution of the previously lacking T cell compartment, allowing analysis of the roles of T cell immunity in humans by comparing before and after gene correction.
Methods: Here we interrogate T cell reconstitution using four forms of high throughput analysis. (1) Estimation of the numbers of transduced progenitor cells by monitoring unique positions of integration of the therapeutic gene transfer vector. (2) Estimation of T cell population structure by sequencing of the recombined T cell receptor (TCR) beta locus. (3) Metagenomic analysis of microbial populations in oropharyngeal, nasopharyngeal, and gut samples. (4) Metagenomic analysis of viral populations in gut samples.
Results: Comparison of progenitor and mature T cell populations allowed estimation of a minimum number of cell divisions needed to generate the observed populations. Analysis of microbial populations showed the effects of immune reconstitution, including normalization of gut microbiota and clearance of viral infections. Metagenomic analysis revealed enrichment of genes for antibiotic resistance in gene-corrected subjects relative to healthy controls, likely a result of higher healthcare exposure.
Conclusions: This multi-omic approach enables the characterization of multiple effects of SCID-X1 gene therapy, including T cell repertoire reconstitution, estimation of numbers of cell divisions between progenitors and daughter T cells, normalization of the microbiome, clearance of microbial pathogens, and modulations in antibiotic resistance gene levels. Together, these results quantify several aspects of the long-term efficacy of gene therapy for SCID-X1. This study includes data from ClinicalTrials.gov numbers NCT01410019, NCT01175239, and NCT01129544.
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http://dx.doi.org/10.1186/s13073-018-0580-z | DOI Listing |
Sci Rep
December 2024
Interventional Oncology, Johnson & Johnson Enterprise Innovation, Inc, 10th Floor 255 Main St, 02142, Cambridge, Boston, MA, USA.
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December 2024
Department of Laboratory Medicine, The Affiliated Hospital of Southwest Medical University, Sichuan Province Engineering Technology Research Center of Molecular Diagnosis of Clinical Diseases, Molecular Diagnosis of Clinical Diseases Key Laboratory of Luzhou, Luzhou, Sichuan, China.
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December 2024
Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Sepsis is defined as a dysfunctional, life-threatening response to infection leading to multiorgan dysfunction and failure. During the past decade, studies have highlighted the relationship between sepsis and aging. However, the role of aging-related mechanisms in the progression and prognosis of sepsis remains unclear.
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December 2024
Precision Medicine Center, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510000, China.
Polyomavirus enhancer activator 3 (PEA3), an ETS transcription factor, has been documented to regulate the development and metastasis of human cancers. Nonetheless, a thorough analysis examining the relationship between the PEA3 subfamily members and tumour development, prognosis, and the tumour microenvironment (TME) across various cancer types has not yet been conducted. The expression profiles and prognostic significance of the PEA3 subfamily were evaluated using data from the GEO, TCGA, and PrognoScan databases, in conjunction with COX regression analyses and the Kaplan-Meier Plotter.
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December 2024
School of Intelligent Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, China.
In recent years, immune checkpoint inhibitors (ICIs) has emerged as a fundamental component of the standard treatment regimen for patients with head and neck squamous cell carcinoma (HNSCC). However, accurately predicting the treatment effectiveness of ICIs for patients at the same TNM stage remains a challenge. In this study, we first combined multi-omics data (mRNA, lncRNA, miRNA, DNA methylation, and somatic mutations) and 10 clustering algorithms, successfully identifying two distinct cancer subtypes (CSs) (CS1 and CS2).
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