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    Home > Active Ingredient News > Blood System > Blood: Genome and transcriptomic characteristics transformed by Richter of chronic lymphocytic leukemia

    Blood: Genome and transcriptomic characteristics transformed by Richter of chronic lymphocytic leukemia

    • Last Update: 2021-01-01
    • Source: Internet
    • Author: User
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    The conversion of chronic lymphocytic leukemia (CLL) to high-level B-cell lymphoma is known as Richter syndrome (RS), which is rare and has a poor prognosis in these patients.
    the study, researchers sequenced the whole genome (WGS) of CLL (PB-CLL) and RS biopsy tissue (tissue-RS) in the blood circulation of 17 patients who participated in clinical trials (CHOP-O).
    study process showed that in tissue-RS, gene mutations in low-risk CLL-driven and DNA Damage Response (DDR) pathways were rich.
    addition, the researchers screened genetic variants that had not previously been reported in RS, including the protein tyrosine phosphatase converter (PTPRD) and tumor necrotizing factor III (TRAF3).
    SNV, InDel, and CNA in patients with Richter syndrome, the researchers found in tissue-RS a kataegis associated with AND unrelated to AIDS that affects the regulatory regions of key immunomodulation genes.
    these include BTG2, CXCR4, NFATC1, PAX5, NOTCH-1, SLC44A5, FCRL3, SELL, TNIP2, and TRIM13.
    changes in the proportion values of cancer cells mutated by so many cells during the RS process, the difference between the overall mutation characteristics of PB-CLL pairs and tissue-RS sample pairs showed that DDR was the main mechanism driving the malignant transformation of CLL.
    analysis of clone anti-converse analysis based on signaling paths shows that genes in MAPK and DDR paths have a high probability of cloning amplification.
    direct comparison of lymph node-CLL and tissue-RS pairs from independent queues by RNA expression spectrum confirmed the difference expression of the same signaling path.
    In summary, the study greatly expanded the previous targeting method through comprehensive analysis of WGS and RNA expression data, broke the limitations of the lack of embryo samples, and helped identify new genomic associations related to RS transformation, which can improve new therapeutic targets.
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