Literature DB >> 33772032

Association between the nucleosome footprint of plasma DNA and neoadjuvant chemotherapy response for breast cancer.

Xu Yang1,2, Geng-Xi Cai3,4, Bo-Wei Han5, Zhi-Wei Guo5, Ying-Song Wu5, Xiaoming Lyu6, Li-Min Huang5, Yuan-Bin Zhang1, Xin Li7,8, Guo-Lin Ye9, Xue-Xi Yang10.   

Abstract

Gene expression signatures have been used to predict the outcome of chemotherapy for breast cancer. The nucleosome footprint of cell-free DNA (cfDNA) carries gene expression information of the original tissues and thus may be used to predict the response to chemotherapy. Here we carried out the nucleosome positioning on cfDNA from 85 breast cancer patients and 85 healthy individuals and two cancer cell lines T-47D and MDA-MB-231 using low-coverage whole-genome sequencing (LCWGS) method. The patients showed distinct nucleosome footprints at Transcription Start Sites (TSSs) compared with normal donors. In order to identify the footprints of cfDNA corresponding with the responses to neoadjuvant chemotherapy in patients, we mapped on nucleosome positions on cfDNA of patients with different responses: responders (pretreatment, n = 28; post-1 cycle, post-3/4 cycles, and post-8 cycles of treatment, n = 12) and nonresponders (pretreatment, n = 10; post-1 cycle, post-3/4 cycles, and post-8 cycles of treatment, n = 10). The coverage depth near TSSs in plasma cfDNA differed significantly between responders and nonresponders at pretreatment, and also after neoadjuvant chemotherapy treatment cycles. We identified 232 TSSs with differential footprints at pretreatment and 321 after treatment and found enrichment in Gene Ontology terms such as cell growth inhibition, tumor suppressor, necrotic cell death, acute inflammatory response, T cell receptor signaling pathway, and positive regulation of vascular endothelial growth factor production. These results suggest that cfDNA nucleosome footprints may be used to predict the efficacy of neoadjuvant chemotherapy for breast cancer patients and thus may provide help in decision making for individual patients.

Entities:  

Year:  2021        PMID: 33772032      PMCID: PMC7997954          DOI: 10.1038/s41523-021-00237-5

Source DB:  PubMed          Journal:  NPJ Breast Cancer        ISSN: 2374-4677


  43 in total

1.  New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada.

Authors:  P Therasse; S G Arbuck; E A Eisenhauer; J Wanders; R S Kaplan; L Rubinstein; J Verweij; M Van Glabbeke; A T van Oosterom; M C Christian; S G Gwyther
Journal:  J Natl Cancer Inst       Date:  2000-02-02       Impact factor: 13.506

2.  Accurate Prediction and Validation of Response to Endocrine Therapy in Breast Cancer.

Authors:  Arran K Turnbull; Laura M Arthur; Lorna Renshaw; Alexey A Larionov; Charlene Kay; Anita K Dunbier; Jeremy S Thomas; Mitch Dowsett; Andrew H Sims; J Michael Dixon
Journal:  J Clin Oncol       Date:  2015-06-01       Impact factor: 44.544

Review 3.  Liquid biopsy in breast cancer: A comprehensive review.

Authors:  Sahar Alimirzaie; Maryam Bagherzadeh; Mohammad R Akbari
Journal:  Clin Genet       Date:  2019-02-27       Impact factor: 4.438

Review 4.  Understanding nucleosome dynamics and their links to gene expression and DNA replication.

Authors:  William K M Lai; B Franklin Pugh
Journal:  Nat Rev Mol Cell Biol       Date:  2017-05-24       Impact factor: 94.444

5.  Inferring expressed genes by whole-genome sequencing of plasma DNA.

Authors:  Peter Ulz; Gerhard G Thallinger; Martina Auer; Ricarda Graf; Karl Kashofer; Stephan W Jahn; Luca Abete; Gunda Pristauz; Edgar Petru; Jochen B Geigl; Ellen Heitzer; Michael R Speicher
Journal:  Nat Genet       Date:  2016-08-29       Impact factor: 38.330

6.  Gene expression profiles predict complete pathologic response to neoadjuvant paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide chemotherapy in breast cancer.

Authors:  M Ayers; W F Symmans; J Stec; A I Damokosh; E Clark; K Hess; M Lecocke; J Metivier; D Booser; N Ibrahim; V Valero; M Royce; B Arun; G Whitman; J Ross; N Sneige; G N Hortobagyi; L Pusztai
Journal:  J Clin Oncol       Date:  2004-05-10       Impact factor: 44.544

7.  Breast Cancer Screening and Diagnosis, Version 3.2018, NCCN Clinical Practice Guidelines in Oncology.

Authors:  Therese B Bevers; Mark Helvie; Ermelinda Bonaccio; Kristine E Calhoun; Mary B Daly; William B Farrar; Judy E Garber; Richard Gray; Caprice C Greenberg; Rachel Greenup; Nora M Hansen; Randall E Harris; Alexandra S Heerdt; Teresa Helsten; Linda Hodgkiss; Tamarya L Hoyt; John G Huff; Lisa Jacobs; Constance Dobbins Lehman; Barbara Monsees; Bethany L Niell; Catherine C Parker; Mark Pearlman; Liane Philpotts; Laura B Shepardson; Mary Lou Smith; Matthew Stein; Lusine Tumyan; Cheryl Williams; Mary Anne Bergman; Rashmi Kumar
Journal:  J Natl Compr Canc Netw       Date:  2018-11       Impact factor: 11.908

8.  Cell-free DNA Comprises an In Vivo Nucleosome Footprint that Informs Its Tissues-Of-Origin.

Authors:  Matthew W Snyder; Martin Kircher; Andrew J Hill; Riza M Daza; Jay Shendure
Journal:  Cell       Date:  2016-01-14       Impact factor: 41.582

9.  On-treatment biomarkers can improve prediction of response to neoadjuvant chemotherapy in breast cancer.

Authors:  Richard J Bownes; Arran K Turnbull; Carlos Martinez-Perez; David A Cameron; Andrew H Sims; Olga Oikonomidou
Journal:  Breast Cancer Res       Date:  2019-06-14       Impact factor: 6.466

10.  Orientation-aware plasma cell-free DNA fragmentation analysis in open chromatin regions informs tissue of origin.

Authors:  Kun Sun; Peiyong Jiang; Suk Hang Cheng; Timothy H T Cheng; John Wong; Vincent W S Wong; Simon S M Ng; Brigette B Y Ma; Tak Y Leung; Stephen L Chan; Tony S K Mok; Paul B S Lai; Henry L Y Chan; Hao Sun; K C Allen Chan; Rossa W K Chiu; Y M Dennis Lo
Journal:  Genome Res       Date:  2019-03       Impact factor: 9.043

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  2 in total

1.  Association between the nucleosome footprint of plasma DNA and neoadjuvant chemotherapy response for breast cancer.

Authors:  Xu Yang; Geng-Xi Cai; Bo-Wei Han; Zhi-Wei Guo; Ying-Song Wu; Xiaoming Lyu; Li-Min Huang; Yuan-Bin Zhang; Xin Li; Guo-Lin Ye; Xue-Xi Yang
Journal:  NPJ Breast Cancer       Date:  2021-03-26

2.  A Deep-Learning Pipeline for TSS Coverage Imputation From Shallow Cell-Free DNA Sequencing.

Authors:  Bo-Wei Han; Xu Yang; Shou-Fang Qu; Zhi-Wei Guo; Li-Min Huang; Kun Li; Guo-Jun Ouyang; Geng-Xi Cai; Wei-Wei Xiao; Rong-Tao Weng; Shun Xu; Jie Huang; Xue-Xi Yang; Ying-Song Wu
Journal:  Front Med (Lausanne)       Date:  2021-12-03
  2 in total

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