Literature DB >> 29684420

Novel cancer gene variants and gene fusions of triple-negative breast cancers (TNBCs) reveal their molecular diversity conserved in the patient-derived xenograft (PDX) model.

Jaeyun Jung1, Kiwon Jang2, Jung Min Ju3, Eunji Lee3, Jong Won Lee4, Hee Jung Kim4, Jisun Kim4, Sae Byul Lee4, Beom Seok Ko4, Byung Ho Son4, Hee Jin Lee5, Gyungyup Gong5, Sei Yeon Ahn4, Jung Kyoon Choi2, Shree Ram Singh6, Suhwan Chang7.   

Abstract

Despite the improved 5-year survival rate of breast cancer, triple-negative breast cancer (TNBC) remains a challenge due to lack of effective targeted therapy and higher recurrence and metastasis than other subtypes. To identify novel druggable targets and to understand its unique biology, we tried to implement 24 patient-derived xenografts (PDXs) of TNBC. The overall success rate of PDX implantation was 45%, much higher than estrogen receptor (ER)-positive cases. Immunohistochemical analysis revealed conserved ER/PR/Her2 negativity (with two exceptions) between the original and PDX tumors. Genomic analysis of 10 primary tumor-PDX pairs with Ion AmpliSeq CCP revealed high degree of variant conservation (85.0%-96.9%) between primary and PDXs. Further analysis showed 44 rare variants with a predicted high impact in 36 genes including Trp53, Pten, Notch1, and Col1a1. Among them, we confirmed frequent Notch1 variant. Furthermore, RNA-seq analysis of 24 PDXs revealed 594 gene fusions, of which 163 were in-frame, including AZGP1-GJC3 and NF1-AARSD1. Finally, western blot analysis of oncogenic signaling proteins supporting molecular diversity of TNBC PDXs. Overall, our report provides a molecular basis for the usefulness of the TNBC PDX model in preclinical study. Published by Elsevier B.V.

Entities:  

Keywords:  Cancer panel; Diversity; Gene fusion; Novel variant; Patient-derived xenografts; Triple-negative breast cancer

Mesh:

Substances:

Year:  2018        PMID: 29684420     DOI: 10.1016/j.canlet.2018.04.020

Source DB:  PubMed          Journal:  Cancer Lett        ISSN: 0304-3835            Impact factor:   8.679


  7 in total

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Journal:  Proc Natl Acad Sci U S A       Date:  2022-07-18       Impact factor: 12.779

2.  HIV-1 Drug Resistance Assay Using Ion Torrent Next Generation Sequencing and On-Instrument End-to-End Analysis Software.

Authors:  Michael T Pyne; Keith E Simmon; Melanie A Mallory; Weston C Hymas; Jeffery Stevenson; Adam P Barker; David R Hillyard
Journal:  J Clin Microbiol       Date:  2022-06-14       Impact factor: 11.677

Review 3.  Patient-Derived Xenograft Models of Breast Cancer and Their Application.

Authors:  Takahiko Murayama; Noriko Gotoh
Journal:  Cells       Date:  2019-06-20       Impact factor: 6.600

4.  Computational inference of cancer-specific vulnerabilities in clinical samples.

Authors:  Kiwon Jang; Min Ji Park; Jae Soon Park; Haeun Hwangbo; Min Kyung Sung; Sinae Kim; Jaeyun Jung; Jong Won Lee; Sei-Hyun Ahn; Suhwan Chang; Jung Kyoon Choi
Journal:  Genome Biol       Date:  2020-06-29       Impact factor: 13.583

5.  LncRNA DANCR contributes to tumor progression via targetting miR-216a-5p in breast cancer: lncRNA DANCR contributes to tumor progression.

Authors:  Weiyang Tao; Chunyang Wang; Bifa Zhu; Guoqiang Zhang; Da Pang
Journal:  Biosci Rep       Date:  2019-04-23       Impact factor: 3.840

6.  Inhibition of p90RSK activation sensitizes triple-negative breast cancer cells to cisplatin by inhibiting proliferation, migration and EMT.

Authors:  Yujin Jin; Diem Thi Ngoc Huynh; Keon Wook Kang; Chang-Seon Myung; Kyung-Sun Heo
Journal:  BMB Rep       Date:  2019-12       Impact factor: 4.778

7.  Genetic heterogeneity and clonal evolution during metastasis in breast cancer patient-derived tumor xenograft models.

Authors:  Kathleen Sprouffske; Grainne Kerr; Cheng Li; Anirudh Prahallad; Ramona Rebmann; Verena Waehle; Ulrike Naumann; Hans Bitter; Michael R Jensen; Francesco Hofmann; Saskia M Brachmann; Stéphane Ferretti; Audrey Kauffmann
Journal:  Comput Struct Biotechnol J       Date:  2020-01-31       Impact factor: 7.271

  7 in total

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