Literature DB >> 33226961

Single cell sequencing reveals cell populations that predict primary resistance to imatinib in chronic myeloid leukemia.

Weilong Zhang1,2, Beibei Yang2, Linqian Weng3, Jiangtao Li3, Jiefei Bai3, Ting Wang3, Jingwen Wang4, Jin Ye4, Hongmei Jing1, Yuchen Jiao2, Xixi Chen5,6, Hui Liu3, Yi-Xin Zeng2,7.   

Abstract

The treatment of chronic myeloid leukemia (CML), a disease caused by t(9;22)(q34;q11) reciprocal translocation, has advanced largely through the use of targeted tyrosine kinase inhibitors (TKIs). To identify molecular differences that might distinguish TKI responders from non-responders, we performed single cell RNA sequencing on cells (n = 41,723 cells) obtained from the peripheral blood of four CML patients at different stages of treatment to generate single cell expression profiles. Analysis of our single cell expression profiles in conjunction with those previously obtained from the bone marrow of additional CML patients and healthy donors (total = 69,263 cells) demonstrated that imatinib treatment significantly altered leukocyte population compositions in both responders and non-responders, and affected the expression profiles of multiple cell populations, including non-neoplastic cell types. Notably, in imatinib poor-responders, patient-specific pre-treatment unique stem/progenitor cells became enriched in peripheral blood compared to the responders. These results indicate that resistance to TKIs might be intrinsic in some CML patients rather than acquired, and that non-neoplastic immune cell types may also play vital roles in dispersing the responsiveness of patients to TKIs. Furthermore, these results demonstrated the potential utility of peripheral blood as a diagnostic tool in the TKI sensitivity of CML patients.

Entities:  

Keywords:  TKI resistance; chronic myeloid leukemia; peripheral immune structure; single cell sequencing; stem cells

Mesh:

Substances:

Year:  2020        PMID: 33226961      PMCID: PMC7803567          DOI: 10.18632/aging.104136

Source DB:  PubMed          Journal:  Aging (Albany NY)        ISSN: 1945-4589            Impact factor:   5.682


  58 in total

1.  S100A16, a ubiquitously expressed EF-hand protein which is up-regulated in tumors.

Authors:  Ingo Marenholz; Claus W Heizmann
Journal:  Biochem Biophys Res Commun       Date:  2004-01-09       Impact factor: 3.575

2.  CD99 plays a major role in the migration of monocytes through endothelial junctions.

Authors:  Alan R Schenkel; Zahra Mamdouh; Xia Chen; Ronald M Liebman; William A Muller
Journal:  Nat Immunol       Date:  2002-01-14       Impact factor: 25.606

3.  Comprehensive Integration of Single-Cell Data.

Authors:  Tim Stuart; Andrew Butler; Paul Hoffman; Christoph Hafemeister; Efthymia Papalexi; William M Mauck; Yuhan Hao; Marlon Stoeckius; Peter Smibert; Rahul Satija
Journal:  Cell       Date:  2019-06-06       Impact factor: 41.582

Review 4.  PD-1/PD-L1 inhibitors.

Authors:  Joel Sunshine; Janis M Taube
Journal:  Curr Opin Pharmacol       Date:  2015-06-02       Impact factor: 5.547

5.  Adoptive transfer of activated marrow-infiltrating lymphocytes induces measurable antitumor immunity in the bone marrow in multiple myeloma.

Authors:  Kimberly A Noonan; Carol A Huff; Janice Davis; M Victor Lemas; Susan Fiorino; Jeffrey Bitzan; Anna Ferguson; Amy Emerling; Leo Luznik; William Matsui; Jonathan Powell; Ephraim Fuchs; Gary L Rosner; Caroline Epstein; Lakshmi Rudraraju; Richard F Ambinder; Richard J Jones; Drew Pardoll; Ivan Borrello
Journal:  Sci Transl Med       Date:  2015-05-20       Impact factor: 17.956

6.  N7 methylation alters hydrogen-bonding patterns of guanine in duplex DNA.

Authors:  Yi Kou; Myong-Chul Koag; Seongmin Lee
Journal:  J Am Chem Soc       Date:  2015-11-02       Impact factor: 15.419

7.  Clinical resistance to STI-571 cancer therapy caused by BCR-ABL gene mutation or amplification.

Authors:  M E Gorre; M Mohammed; K Ellwood; N Hsu; R Paquette; P N Rao; C L Sawyers
Journal:  Science       Date:  2001-06-21       Impact factor: 47.728

8.  Monitoring patients in complete cytogenetic remission after treatment of CML in chronic phase with imatinib: patterns of residual leukaemia and prognostic factors for cytogenetic relapse.

Authors:  D Marin; J Kaeda; R Szydlo; S Saunders; A Fleming; J Howard; C Andreasson; M Bua; E Olavarria; A Rahemtulla; F Dazzi; E Kanfer; J M Goldman; J F Apperley
Journal:  Leukemia       Date:  2005-04       Impact factor: 11.528

9.  The hematopoietic stem cell in chronic phase CML is characterized by a transcriptional profile resembling normal myeloid progenitor cells and reflecting loss of quiescence.

Authors:  I Bruns; A Czibere; J C Fischer; F Roels; R-P Cadeddu; S Buest; D Bruennert; A N Huenerlituerkoglu; N H Stoecklein; R Singh; L F Zerbini; M Jäger; G Kobbe; N Gattermann; R Kronenwett; B Brors; R Haas
Journal:  Leukemia       Date:  2009-01-22       Impact factor: 11.528

10.  Reversed graph embedding resolves complex single-cell trajectories.

Authors:  Xiaojie Qiu; Qi Mao; Ying Tang; Li Wang; Raghav Chawla; Hannah A Pliner; Cole Trapnell
Journal:  Nat Methods       Date:  2017-08-21       Impact factor: 47.990

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.