Literature DB >> 12969976

Identification of genes modulated in multiple myeloma using genetically identical twin samples.

Nikhil C Munshi1, Teru Hideshima, Daniel Carrasco, Masood Shammas, Daniel Auclair, Faith Davies, Nicholas Mitsiades, Constantine Mitsiades, Ryung Suk Kim, Cheng Li, S Vincent Rajkumar, Rafael Fonseca, Lief Bergsagel, Dharminder Chauhan, Kenneth C Anderson.   

Abstract

Genetic heterogeneity between individuals confounds the comparison of gene profiling of multiple myeloma (MM) cells versus normal plasma cells (PCs). To overcome this barrier, we compared the gene expression profile of CD138+ MM cells from a patient bone marrow (BM) sample with CD138+ PCs from a genetically identical twin BM sample using microarray profiling. Two hundred and ninety-six genes were up-regulated and 103 genes were down-regulated at least 2-fold in MM cells versus normal twin PCs. Highly expressed genes in MM cells included cell survival pathway genes such as mcl-1, dad-1, caspase 8, and FADD-like apoptosis regulator (FLIP); oncogenes/transcriptional factors such as Jun-D, Xbp-1, calmodulin, Calnexin, and FGFR-3; stress response and ubiquitin/proteasome pathway-related genes and various ribosomal genes reflecting increased metabolic and translational activity. Genes that were down-regulated in MM cells versus healthy twin PCs included RAD51, killer cell immunoglobulin-like receptor protein, and apoptotic protease activating factor. Microarray results were further confirmed by Western blot analyses, immunohistochemistry, fluorescent in situ hybridization (FISH), and functional assays of telomerase activity and bone marrow angiogenesis. This molecular profiling provides potential insights into mechanisms of malignant transformation in MM. For example, FGFR3, xbp-1, and both mcl-1 and dad-1 may mediate transformation, differentiation, and survival, respectively, and may have clinical implications. By identifying genes uniquely altered in MM cells compared with normal PCs in an identical genotypic background, the current study provides the framework to identify novel therapeutic targets.

Entities:  

Mesh:

Substances:

Year:  2003        PMID: 12969976     DOI: 10.1182/blood-2003-02-0402

Source DB:  PubMed          Journal:  Blood        ISSN: 0006-4971            Impact factor:   22.113


  53 in total

1.  NF-κB signaling is required for XBP1 (unspliced and spliced)-mediated effects on antiestrogen responsiveness and cell fate decisions in breast cancer.

Authors:  Rong Hu; Anni Warri; Lu Jin; Alan Zwart; Rebecca B Riggins; Hong-Bin Fang; Robert Clarke
Journal:  Mol Cell Biol       Date:  2014-11-03       Impact factor: 4.272

2.  Blockade of XBP1 splicing by inhibition of IRE1α is a promising therapeutic option in multiple myeloma.

Authors:  Naoya Mimura; Mariateresa Fulciniti; Gullu Gorgun; Yu-Tzu Tai; Diana Cirstea; Loredana Santo; Yiguo Hu; Claire Fabre; Jiro Minami; Hiroto Ohguchi; Tanyel Kiziltepe; Hiroshi Ikeda; Yutaka Kawano; Maureen French; Martina Blumenthal; Victor Tam; Nathalie L Kertesz; Uriel M Malyankar; Mark Hokenson; Tuan Pham; Qingping Zeng; John B Patterson; Paul G Richardson; Nikhil C Munshi; Kenneth C Anderson
Journal:  Blood       Date:  2012-04-26       Impact factor: 22.113

3.  Telomere maintenance in laser capture microdissection-purified Barrett's adenocarcinoma cells and effect of telomerase inhibition in vivo.

Authors:  Masood A Shammas; Aamer Qazi; Ramesh B Batchu; Robert C Bertheau; Jason Y Y Wong; Manjula Y Rao; Madhu Prasad; Diptiman Chanda; Selvarangan Ponnazhagan; Kenneth C Anderson; Christopher P Steffes; Nikhil C Munshi; Immaculata De Vivo; David G Beer; Sergei Gryaznov; Donald W Weaver; Raj K Goyal
Journal:  Clin Cancer Res       Date:  2008-08-01       Impact factor: 12.531

4.  Angiogenesis and multiple myeloma.

Authors:  Nicola Giuliani; Paola Storti; Marina Bolzoni; Benedetta Dalla Palma; Sabrina Bonomini
Journal:  Cancer Microenviron       Date:  2011-07-07

5.  Specific killing of multiple myeloma cells by (-)-epigallocatechin-3-gallate extracted from green tea: biologic activity and therapeutic implications.

Authors:  Masood A Shammas; Paola Neri; Hemanta Koley; Ramesh B Batchu; Robert C Bertheau; Vidit Munshi; Rao Prabhala; Mariateresa Fulciniti; Yu Tzu Tai; Steven P Treon; Raj K Goyal; Kenneth C Anderson; Nikhil C Munshi
Journal:  Blood       Date:  2006-06-29       Impact factor: 22.113

6.  Definition of a multiple myeloma progenitor population in mice driven by enforced expression of XBP1s.

Authors:  Joshua Kellner; Caroline Wallace; Bei Liu; Zihai Li
Journal:  JCI Insight       Date:  2019-04-04

7.  Caspase polymorphisms and genetic susceptibility to multiple myeloma.

Authors:  H Dean Hosgood; Dalsu Baris; Yawei Zhang; Yong Zhu; Tongzhang Zheng; Meredith Yeager; Robert Welch; Shelia Zahm; Stephen Chanock; Nathaniel Rothman; Qing Lan
Journal:  Hematol Oncol       Date:  2008-09       Impact factor: 5.271

8.  Dysfunctional homologous recombination mediates genomic instability and progression in myeloma.

Authors:  Masood A Shammas; Robert J Shmookler Reis; Hemanta Koley; Ramesh B Batchu; Cheng Li; Nikhil C Munshi
Journal:  Blood       Date:  2008-12-02       Impact factor: 22.113

9.  Cyclin K and cyclin D1b are oncogenic in myeloma cells.

Authors:  Véronique Marsaud; Guergana Tchakarska; Geoffroy Andrieux; Jian-Miao Liu; Doulaye Dembele; Bernard Jost; Joanna Wdzieczak-Bakala; Jack-Michel Renoir; Brigitte Sola
Journal:  Mol Cancer       Date:  2010-05-10       Impact factor: 27.401

10.  A list of candidate cancer biomarkers for targeted proteomics.

Authors:  Malu Polanski; N Leigh Anderson
Journal:  Biomark Insights       Date:  2007-02-07
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.