Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 5 de 5
Filter
Add filters








Language
Year range
1.
Article in Chinese | WPRIM | ID: wpr-879584

ABSTRACT

OBJECTIVE@#To detect fusion gene with pathological significance in a patient with refractory and relapsed acute B cell lymphoblastic leukemia (B-ALL) and to explore its laboratory and clinical characteristics.@*METHODS@#Transcriptome sequencing was used to detect potential fusion transcripts. Other laboratory results and clinical data of the patient were also analyzed.@*RESULTS@#The patient was found to harbor TCF3 exon 17-ZNF384 exon 7 in-frame fusion transcript. The minimal residual disease (MRD) has remained positive after multiple chemotherapy protocols including CD19-, CD22- targeted chimeric antigen receptor T cells immunotherapy. The patient eventually achieved complete remission and sustained MRD negativity after allogeneic hemopoietic stem cell transplantation (allo-HSCT).@*CONCLUSION@#Transcriptome sequencing can effectively detect potential fusion genes with clinical significance in leukemia. TCF3-ZNF384 positive B-ALL has unique laboratory and clinical characteristics, may not well respond to chemotherapy and immunotherapy, and is more likely to relapse. Timely allo-HSCT treatment may help such patients to achieve long-term disease-free survival. TCF3-ZNF384 positive B-ALL is not uncommon in pediatric patients but has not been effectively identified.


Subject(s)
B-Lymphocytes , Basic Helix-Loop-Helix Transcription Factors/genetics , Child , Hematopoietic Stem Cell Transplantation , Humans , Laboratories , Precursor Cell Lymphoblastic Leukemia-Lymphoma/therapy , Trans-Activators/genetics , Transcriptome
2.
Article in Chinese | WPRIM | ID: wpr-799285

ABSTRACT

The new wave of artificial intelligence pushed by deep learning algorithms has dramatically promoted the development of big data analysis technology. On the other hand, advances in life sciences represented by high-throughput genome sequencing have provided massive medical data. Artificial intelligence technology has also provided a powerful tool for hematological malignancy research. This article introduces related research progress in the 61st American Society of Hematology Annual Meeting.

3.
Journal of Leukemia & Lymphoma ; (12): 326-330, 2020.
Article in Chinese | WPRIM | ID: wpr-862848

ABSTRACT

Objective:To investigate the infection spectrum revealed by metagenomics high-throughput next-generation sequencing (mNGS), and to provide a reference for infection diagnosis after allogeneic hematopoietic stem cell transplantation (allo-HSCT).Methods:A total of 64 patients who developed systemic or local infection symptoms after allo-HSCT in Hebei Yanda Lu Daopei Hospital from January 2018 to November 2018 were enrolled. Gene sequences of pathogenic microorganisms in blood, cerebrospinal fluid and bronchoalveolar fluid specimens were detected by using mNGS. The pathogenic microorganisms or suspected pathogens were determined based on the clinical manifestations of patients.Results:There were 97 samples of mNGS detection for 64 patients who underwent allo-HSCT. The most common gram-positive bacteria were staphylococcus haemolyticus (19 times) and staphylococcus (14 times), and the most common gram-negative bacterium was acinetobacter baumannii (8 times). The most common viruses were cytomegalovirus, EB virus and Torque teno virus (35, 22 and 23 times, respectively), and the most common fungi were malassezia globus (14 times) and candida parapsilosis (8 times). There were 3 mycobacterium tuberculosis complexes detected in 3 patients with acute myeloid leukemia who received allo-HSCT. Mycoplasma orale was detected in one patient's sputum, and none parasite was detected.Conclusion:mNGS can comprehensively reveal the infection spectrum of hematologic diseases after allo-HSCT, especially for pathogenic microorganisms that are rare or difficult to cultivate, and it can effectively help the diagnosis of clinically infectious pathogens.

4.
Article in Chinese | WPRIM | ID: wpr-862786

ABSTRACT

The new wave of artificial intelligence pushed by deep learning algorithms has dramatically promoted the development of big data analysis technology. On the other hand, advances in life sciences represented by high-throughput genome sequencing have provided massive medical data. Artificial intelligence technology has also provided a powerful tool for hematological malignancy research. This article introduces related research progress in the 61st American Society of Hematology Annual Meeting.

5.
Article in Chinese | WPRIM | ID: wpr-691612

ABSTRACT

Neoantigens, as the products of gene mutations in tumor cells, are specific antigen expressed on the surface of tumor cells. They can be the targets of immuno-cell therapies with high specificity and safety. Immunotherapies based on tumor neoantigens became the new research hotspot as results of the applications of genomic sequencing technologies and the development of neoantigens prediction techniques. In this paper, the applied prospect of neoantigens in hematological malignancies is discussed based on the research progress in the last few years and the relevant reports from the 59th American Society of Hematology Annual Meeting.

SELECTION OF CITATIONS
SEARCH DETAIL