Multiple Interacting Oncogenes on the 8p11-p12 Amplicon in Human Breast Cancer

Yang, Zunhua; Streicher, Katie; Ray, Michael E.; Abrams, Judith; Ethier, Stephen P.

doi:10.1158/0008-5472.can-06-2946

Cited by 112 publications

(147 citation statements)

References 49 publications

Supporting

Mentioning

136

Contrasting

Unclassified

Order By: Relevance

“…This is not the case in the IPH-926 cells, since they lack overexpression of FGFR1 mRNA and FGFR1 protein, and were not sensitive to the FGFR1 inhibitor SU5402. Genes such BAG4, C8orf4, and UNC5D might be the target of the genomic alterations on chromosome 8 [45,46].…”

Section: Discussionmentioning

confidence: 99%

Comprehensive genetic and functional characterization of IPH‐926: a novel CDH1‐null tumour cell line from human lobular breast cancer

Christgen

Bruchhardt

Hadamitzky

et al. 2009

The Journal of Pathology

View full text Add to dashboard Cite

show abstract

Section: Discussionmentioning

confidence: 99%

Comprehensive genetic and functional characterization of IPH‐926: a novel CDH1‐null tumour cell line from human lobular breast cancer

Christgen

Bruchhardt

Hadamitzky

et al. 2009

The Journal of Pathology

View full text Add to dashboard Cite

show abstract

“…There Table 5 Phosphoric ester hydrolase activity CTDSPL2, CTDSPL, PON2, PFKFB1, PFKFB2, IMPA2, INPP5B, NT5C1B, NT5E, DLG7, CTDP1, CILP, PPAP2B, PPAP2C, DLG1, LCK, PPM1A, PPM1H, RGS12, TIAM1, BAG4, MS4A1, DCLK1, BRAF, STYX Table 5 that are implicated to play roles in the progression of breast cancer or other cancers, including BDKRB2 (Greco et al, 2005), PLCB1 (Naor, 2009), PLD1 (Eisen and Brown, 2002), GPLD1 (Derevianko et al, 1996;Williams et al, 2001), EXO1 (Naderi et al, 2007), ANG (Campo et al, 2005), ISG20/HEM45 (Pentecost, 1998), AZGP1/ZAG (Hassan et al, 2009), ZKSCAN1 (Pennanen et al, 2009), REXO2 (Flanagan et al, 2009), CTDSPL (Murabito et al, 2007), NT5E (Zhou et al, 2007), DLG1 (Fuja et al, 2004), PPM1A (Lin et al, 2006), TIAM1 (Lane et al, 2008), BAG4 (Yang et al, 2006), BRAF (Hollestelle, et al, 2007), CLDN4 (Kulka et al, 2009), F3/TF (Amirkhosravi et al, 1998), FZD1 (Benhaj et al, 2006), NGFR (Reis-Filho et al, 2006), LEFR , RAC1 , PLXNB1 (Rody et al, 2007), IGHG1 (Kabbage et al, 2008), IGHG3 (Bin Amer et al, 2008), TLR3 (Salaun et al, 2006), FBN1 , DUSP4 (Venter et al, 2005), PTPN3 (Wang et al, 2004), CDKN3/KAP (Lee et al, 2000), and etc.…”

Section: Resultsmentioning

confidence: 99%

Integrative Analysis of Microarray Data with Gene Ontology to Select Perturbed Molecular Functions using Gene Ontology Functional Code

Kim¹,

Choi²,

Yoon³

2009

Genomics & Informatics

View full text Add to dashboard Cite

A systems biology approach for the identification of perturbed molecular functions is required to understand the complex progressive disease such as breast cancer.In this study, we analyze the microarray data with Gene Ontology terms of molecular functions to select perturbed molecular functional modules in breast cancer tissues based on the definition of Gene ontology Functional Code. The Gene Ontology is three structured vocabularies describing genes and its products in terms of their associated biological processes, cellular components and molecular functions. The Gene Ontology is hierarchically classified as a directed acyclic graph. However, it is difficult to visualize Gene Ontology as a directed tree since a Gene Ontology term may have more than one parent by providing multiple paths from the root. Therefore, we applied the definition of Gene Ontology codes by defining one or more GO code(s) to each GO term to visualize the hierarchical classification of GO terms as a network. The selected molecular functions could be considered as perturbed molecular functional modules that putatively contributes to the progression of disease. We evaluated the method by analyzing microarray dataset of breast cancer tissues; i.e., normal and invasive breast cancer tissues. Based on the integration approach, we selected several interesting perturbed molecular functions that are implicated in the progression of breast cancers. Moreover, these selected molecular functions include several known breast cancer-related genes. It is concluded from this study that the present strategy is capable of selecting perturbed molecular functions that putatively play roles in the progression of diseases and provides an improved interpretability of GO terms based on the definition of Gene Ontology codes.

show abstract

“…All candidate genes were in the 8p11-12 region, where FGFR1 resides, and are therefore potentially interacting oncogenes. 37,38,63e65 Some have transforming properties when overexpressed 63,65 (eg, LSM1, BAG4, WHSC1L1, and DDHD2). BRF2 encodes a RNA polymerase III transcription initiation factor, and RAB11-FIP1 is a regulator of RAB GTPases, which regulate virtually all steps of membrane traffic, whereas DDHD2 and WHSC1L1 may play a role in cell proliferation and survival.…”

Section: Discussionmentioning

confidence: 99%

An mRNA Gene Expression–Based Signature to Identify FGFR1-Amplified Estrogen Receptor–Positive Breast Tumors

Luo

Liu

Leung

et al. 2017

The Journal of Molecular Diagnostics

View full text Add to dashboard Cite

Fibroblast growth factor receptor 1 (FGFR1) amplification drives poor prognosis and is an emerging therapeutic target. We sought to construct a multigene mRNA expression signature to efficiently identify FGFR1-amplified estrogen receptorepositive (ER þ ) breast tumors. Five independent breast tumor series were analyzed. Genes discriminative for FGFR1 amplification were screened transcriptomewide by receiver operating characteristic analyses. The METABRIC series was leveraged to construct/ evaluate four approaches to signature composition. A locked-down signature was validated with 651 ER þ formalin-fixed, paraffin-embedded tissues (the University of British Columbiaetamoxifen cohort). A NanoString nCounter assay was designed to profile selected genes. For a gold standard, FGFR1 amplification was determined by fluorescent in situ hybridization (FISH). Prognostic effects of FGFR1 amplification were assessed by survival analyses. Eight 8p11-12 genes (ASH2L, BAG4, BRF2, DDHD2, LSM1, PROSC, RAB11FIP1, and WHSC1L1) together with the a priori selected FGFR1 gene, highly discriminated FGFR1 amplification (area under the receiver operating characteristic curve !0.82, all genes and all cohorts). The nine-gene signature Call-FGFR1-amp accurately identified FGFR1 FISHamplified ER þ tumors in the University of British Columbiaetamoxifen cohort (specificity, 0.94; sensitivity, 0.96) and exhibited prognostic effects (disease-specific survival hazard ratio, 1.57; 95% CI, 1.14e2.16; P Z 0.005). Call-FGFR1-amp includes several understudied 8p11-12 amplicon-driven oncogenes and accurately identifies FGFR1-amplified ER þ breast tumors. Our study demonstrates an efficient approach to diagnosing rare amplified therapeutic targets with FISH as a confirmatory assay.

show abstract

Multiple Interacting Oncogenes on the 8p11-p12 Amplicon in Human Breast Cancer

Cited by 112 publications

References 49 publications

Comprehensive genetic and functional characterization of IPH‐926: a novel CDH1‐null tumour cell line from human lobular breast cancer

Comprehensive genetic and functional characterization of IPH‐926: a novel CDH1‐null tumour cell line from human lobular breast cancer

Integrative Analysis of Microarray Data with Gene Ontology to Select Perturbed Molecular Functions using Gene Ontology Functional Code

An mRNA Gene Expression–Based Signature to Identify FGFR1-Amplified Estrogen Receptor–Positive Breast Tumors

Contact Info

Product

Resources

About