Literature DB >> 21937081

Gene expression signatures differentiate adenocarcinoma of lung and breast origin in effusions.

Ben Davidson1, Helene Tuft Stavnes, Björn Risberg, Jahn M Nesland, Jeremias Wohlschlaeger, Yanqin Yang, Ie-Ming Shih, Tian-Li Wang.   

Abstract

Lung and breast adenocarcinoma at advanced stages commonly involve the serosal cavities, giving rise to malignant effusions. The aim of the present study was to compare the global gene expression patterns of metastases from these 2 malignancies, to expand and improve the diagnostic panel of biomarkers currently available for their differential diagnosis, as well as to define type-specific biological targets. Gene expression profiles of 7 breast and 4 lung adenocarcinoma effusions were analyzed using the HumanRef-8 BeadChip from Illumina. Differentially expressed candidate genes were validated using quantitative real-time polymerase chain reaction and immunohistochemistry. Unsupervised hierarchical clustering using all 54,675 genes in the array separated lung from breast adenocarcinoma samples. We identified 289 unique probes that were significantly differentially expressed in the 2 cancers by greater than 2-fold using moderated t statistics, of which 65 and 224 were overexpressed in breast and lung adenocarcinoma, respectively. Genes overexpressed in breast adenocarcinoma included TFF1, TFF3, FOXA1, CA12, PITX1, RARRES1, CITED4, MYC, TFAP2A, EFHD1, TOB1, SPDEF, FASN, and TH. Genes overexpressed in lung adenocarcinoma included TITF1, SFTPG, MMP7, EVA1, GPR116, HOP, SCGB3A2, and MET. The differential expression of 15 genes was validated by quantitative real-time PCR, and differences in 8 gene products were confirmed by immunohistochemistry. Expression profiling distinguishes breast adenocarcinoma from lung adenocarcinoma and identifies genes that are differentially expressed in these 2 tumor types. The molecular signatures unique to these cancers may facilitate their differential diagnosis and may provide a molecular basis for therapeutic target discovery.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21937081     DOI: 10.1016/j.humpath.2011.06.015

Source DB:  PubMed          Journal:  Hum Pathol        ISSN: 0046-8177            Impact factor:   3.466


  9 in total

1.  Identification of differentially-expressed genes between early-stage adenocarcinoma and squamous cell carcinoma lung cancer using meta-analysis methods.

Authors:  Tianjiao Wang; Lei Zhang; Pu Tian; Suyan Tian
Journal:  Oncol Lett       Date:  2017-03-10       Impact factor: 2.967

Review 2.  Adhesion GPCRs in Tumorigenesis.

Authors:  Gabriela Aust; Dan Zhu; Erwin G Van Meir; Lei Xu
Journal:  Handb Exp Pharmacol       Date:  2016

3.  PITX1, a specificity determinant in the HIF-1α-mediated transcriptional response to hypoxia.

Authors:  Sharon Mudie; Daniel Bandarra; Michael Batie; John Biddlestone; Sonia Moniz; Brian Ortmann; Alena Shmakova; Sonia Rocha
Journal:  Cell Cycle       Date:  2014       Impact factor: 4.534

4.  Serum TFF1 and TFF3 but not TFF2 are higher in women with breast cancer than in women without breast cancer.

Authors:  Yuko Ishibashi; Hiroshi Ohtsu; Masako Ikemura; Yasuko Kikuchi; Takayoshi Niwa; Kotoe Nishioka; Yoshihiro Uchida; Hirona Miura; Susumu Aikou; Toshiaki Gunji; Nobuyuki Matsuhashi; Yasukazu Ohmoto; Takeshi Sasaki; Yasuyuki Seto; Toshihisa Ogawa; Keiichiro Tada; Sachiyo Nomura
Journal:  Sci Rep       Date:  2017-07-07       Impact factor: 4.379

5.  Combination of azacitidine and trichostatin A decreased the tumorigenic potential of lung cancer cells.

Authors:  Yang Yang; Wei Yin; Fengying Wu; Jiang Fan
Journal:  Onco Targets Ther       Date:  2017-06-14       Impact factor: 4.147

6.  Epithelial V-like antigen 1 promotes hepatocellular carcinoma growth and metastasis via the ERBB-PI3K-AKT pathway.

Authors:  QianZhi Ni; Zhenhua Chen; Qianwen Zheng; Dong Xie; Jing-Jing Li; Shuqun Cheng; Xingyuan Ma
Journal:  Cancer Sci       Date:  2020-03-10       Impact factor: 6.716

7.  Deep learning assisted multi-omics integration for survival and drug-response prediction in breast cancer.

Authors:  Vidhi Malik; Yogesh Kalakoti; Durai Sundar
Journal:  BMC Genomics       Date:  2021-03-24       Impact factor: 3.969

8.  Epigenetic study of early breast cancer (EBC) based on DNA methylation and gene integration analysis.

Authors:  Wenshan Zhang; Haoqi Wang; Yixin Qi; Sainan Li; Cuizhi Geng
Journal:  Sci Rep       Date:  2022-02-07       Impact factor: 4.379

9.  Integrative genome-wide gene expression profiling of clear cell renal cell carcinoma in Czech Republic and in the United States.

Authors:  Magdalena B Wozniak; Florence Le Calvez-Kelm; Behnoush Abedi-Ardekani; Graham Byrnes; Geoffroy Durand; Christine Carreira; Jocelyne Michelon; Vladimir Janout; Ivana Holcatova; Lenka Foretova; Antonin Brisuda; Fabienne Lesueur; James McKay; Paul Brennan; Ghislaine Scelo
Journal:  PLoS One       Date:  2013-03-05       Impact factor: 3.240

  9 in total

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