Literature DB >> 17938484

Clinical implication of genome-wide profiling in diffuse large B-cell lymphoma and other subtypes of B-cell lymphoma.

Javeed Iqbal1, Shantaram Joshi, Kavita N Patel, Sofi I Javed, Can Kucuk, Afeera Aabida, Francesco d'Amore, Kai Fu.   

Abstract

The differentiation of lymphoid cells is tightly regulated by transcription factors at various stages during their development. During the maturation processes, different genomic alterations or aberrations such as chromosomal translocation, mutation and deletions may occur that can eventually result in distinct biological and clinical tumors. The different differentiation stages create heterogeneity in lymphoid malignancies, which can complicate the diagnosis. The initial diagnostic scheme for lymphoid diseases was coined by Rappaport followed by Revised European and American Classification of Lymphoid Neoplasms (REAL) and World Health Organization (WHO) classifications. These classification methods were based on histological, immunophenotypic and cytogenetic markers and widely accepted by pathologists and oncologists worldwide. During last several decades, great progress has been made in understanding the etiology, pathogenesis and molecular biology of malignant lymphoma. However, detailed knowledge in the molecular mechanism of lymphomagenesis is largely unknown. New therapeutic protocols based on the new classification have been on clinical trials, but with little success. Therefore, it is imperative to understand the basic biology of the tumor at molecular level. One important approach will be to measure the activity of the tumor genome and this can partly be achieved by the measurement of whole cellular mRNA. One of the key technologies to perform a high-throughput analysis is DNA microarray technology. The genome-wide transcriptional measurement, also called gene expression profile (GEP) can accurately define the biological phenotype of the tumor. In this review, important discoveries made by genome-wide GEP in understanding the biology of lymphoma and additionally the diagnostic and prognostic value of microarrays are discussed.

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Year:  2007        PMID: 17938484     DOI: 10.4103/0019-509x.35814

Source DB:  PubMed          Journal:  Indian J Cancer        ISSN: 0019-509X            Impact factor:   1.224


  4 in total

1.  Global microRNA expression profiling uncovers molecular markers for classification and prognosis in aggressive B-cell lymphoma.

Authors:  Javeed Iqbal; Yulei Shen; Xin Huang; Yanyan Liu; Laura Wake; Cuiling Liu; Karen Deffenbacher; Cynthia M Lachel; Chao Wang; Joseph Rohr; Shuangping Guo; Lynette M Smith; George Wright; Sharathkumar Bhagavathi; Karen Dybkaer; Kai Fu; Timothy C Greiner; Julie M Vose; Elaine Jaffe; Lisa Rimsza; Andreas Rosenwald; German Ott; Jan Delabie; Elias Campo; Rita M Braziel; James R Cook; Raymond R Tubbs; James O Armitage; Dennis D Weisenburger; Louis M Staudt; Randy D Gascoyne; Timothy W McKeithan; Wing C Chan
Journal:  Blood       Date:  2014-12-10       Impact factor: 22.113

2.  NF-kappaB down-regulates expression of the B-lymphoma marker CD10 through a miR-155/PU.1 pathway.

Authors:  Ryan C Thompson; Melanie Herscovitch; Ian Zhao; Tyler J Ford; Thomas D Gilmore
Journal:  J Biol Chem       Date:  2010-10-14       Impact factor: 5.157

3.  Cyclin C is a haploinsufficient tumour suppressor.

Authors:  Na Li; Anne Fassl; Joel Chick; Hiroyuki Inuzuka; Xiaoyu Li; Marc R Mansour; Lijun Liu; Haizhen Wang; Bryan King; Shavali Shaik; Alejandro Gutierrez; Alban Ordureau; Tobias Otto; Taras Kreslavsky; Lukas Baitsch; Leah Bury; Clifford A Meyer; Nan Ke; Kristin A Mulry; Michael J Kluk; Moni Roy; Sunkyu Kim; Xiaowu Zhang; Yan Geng; Agnieszka Zagozdzon; Sarah Jenkinson; Rosemary E Gale; David C Linch; Jean J Zhao; Charles G Mullighan; J Wade Harper; Jon C Aster; Iannis Aifantis; Harald von Boehmer; Steven P Gygi; Wenyi Wei; A Thomas Look; Piotr Sicinski
Journal:  Nat Cell Biol       Date:  2014-10-26       Impact factor: 28.824

4.  Machine learning-based classification of diffuse large B-cell lymphoma patients by eight gene expression profiles.

Authors:  Shuangtao Zhao; Xiaoli Dong; Wenzhi Shen; Zhen Ye; Rong Xiang
Journal:  Cancer Med       Date:  2016-02-11       Impact factor: 4.452

  4 in total

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