1
|
Zhao M, Howard EW, Parris AB, Guo Z, Zhao Q, Yang X. Alcohol promotes migration and invasion of triple-negative breast cancer cells through activation of p38 MAPK and JNK. Mol Carcinog 2016; 56:849-862. [PMID: 27533114 DOI: 10.1002/mc.22538] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2016] [Revised: 08/05/2016] [Accepted: 08/15/2016] [Indexed: 12/26/2022]
Abstract
Although alcohol is an established breast cancer risk factor, the underlying mechanisms remain unclear. Previous studies examined the general association between alcohol consumption and breast cancer risk; however, the risk for different breast cancer subtypes has been rarely reported. Triple-negative breast cancer (TNBC) is a subtype of breast cancer lacking hormone receptors and HER2 expression, and having poor prognosis. Understanding the molecular mechanisms of TNBC etiology remains a significant challenge. In this study, we investigated cellular responses to alcohol in two TNBC cell lines, MDA-MB-231 and MDA-MB-468. Our results showed that alcohol at low concentrations (0.025-0.1% v/v) induced cell proliferation, migration, and invasion in 1% FBS-containing medium. Molecular analysis indicated that these phenotypic changes were associated with alcohol-induced reactive oxygen species production and increased p38 and JNK phosphorylation. Likewise, p38 or JNK inhibition attenuated alcohol-induced cell migration and invasion. We revealed that alcohol treatment activated/phosphorylated NF-κB regulators and increased transcription of NF-κB-targeted genes. While examining the role of acetaldehyde, the major alcohol metabolite, in alcohol-associated responses in TNBC cells, we saw that acetaldehyde induced cell migration, invasion, and increased phospho-p38, phospho-JNK, and phospho-IκBα in a pattern similar to alcohol treatment. Taken together, we established that alcohol promotes TNBC cell proliferation, migration, and invasion in vitro. The underlying mechanisms involve the induction of oxidative stress and the activation of NF-κB signaling. In particular, the activation of p38 and JNK plays a pivotal role in alcohol-induced cellular responses. These results will advance our understanding of alcohol-mediated development and promotion of TNBC. © 2016 Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- Ming Zhao
- Department of Biology, Julius L. Chambers Biomedical/Biotechnology Research Institute, North Carolina Central University, Kannapolis, North Carolina
| | - Erin W Howard
- Department of Biology, Julius L. Chambers Biomedical/Biotechnology Research Institute, North Carolina Central University, Kannapolis, North Carolina
| | - Amanda B Parris
- Department of Biology, Julius L. Chambers Biomedical/Biotechnology Research Institute, North Carolina Central University, Kannapolis, North Carolina
| | - Zhiying Guo
- Department of Biology, Julius L. Chambers Biomedical/Biotechnology Research Institute, North Carolina Central University, Kannapolis, North Carolina
| | - Qingxia Zhao
- Department of Biology, Julius L. Chambers Biomedical/Biotechnology Research Institute, North Carolina Central University, Kannapolis, North Carolina
| | - Xiaohe Yang
- Department of Biology, Julius L. Chambers Biomedical/Biotechnology Research Institute, North Carolina Central University, Kannapolis, North Carolina
| |
Collapse
|
2
|
Bollig-Fischer A, Marchetti L, Mitrea C, Wu J, Kruger A, Manca V, Drăghici S. Modeling time-dependent transcription effects of HER2 oncogene and discovery of a role for E2F2 in breast cancer cell-matrix adhesion. ACTA ACUST UNITED AC 2014; 30:3036-43. [PMID: 25028721 DOI: 10.1093/bioinformatics/btu400] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
MOTIVATION Oncogenes are known drivers of cancer phenotypes and targets of molecular therapies; however, the complex and diverse signaling mechanisms regulated by oncogenes and potential routes to targeted therapy resistance remain to be fully understood. To this end, we present an approach to infer regulatory mechanisms downstream of the HER2 driver oncogene in SUM-225 metastatic breast cancer cells from dynamic gene expression patterns using a succession of analytical techniques, including a novel MP grammars method to mathematically model putative regulatory interactions among sets of clustered genes. RESULTS Our method highlighted regulatory interactions previously identified in the cell line and a novel finding that the HER2 oncogene, as opposed to the proto-oncogene, upregulates expression of the E2F2 transcription factor. By targeted gene knockdown we show the significance of this, demonstrating that cancer cell-matrix adhesion and outgrowth were markedly inhibited when E2F2 levels were reduced. Thus, validating in this context that upregulation of E2F2 represents a key intermediate event in a HER2 oncogene-directed gene expression-based signaling circuit. This work demonstrates how predictive modeling of longitudinal gene expression data combined with multiple systems-level analyses can be used to accurately predict downstream signaling pathways. Here, our integrated method was applied to reveal insights as to how the HER2 oncogene drives a specific cancer cell phenotype, but it is adaptable to investigate other oncogenes and model systems. AVAILABILITY AND IMPLEMENTATION Accessibility of various tools is listed in methods; the Log-Gain Stoichiometric Stepwise algorithm is accessible at http://www.cbmc.it/software/Software.php.
Collapse
Affiliation(s)
- Aliccia Bollig-Fischer
- Barbara Ann Karmanos Cancer Institute and Department of Oncology, Wayne State University, Detroit, MI 48201, USA, Department of Computer Science, University of Verona, 37134 Verona, Italy, The Microsoft Research-University of Trento Centre for Computational and Systems Biology, 38068 Rovereto, Italy, Department of Computer Science, Wayne State University and Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI 48201, USA Barbara Ann Karmanos Cancer Institute and Department of Oncology, Wayne State University, Detroit, MI 48201, USA, Department of Computer Science, University of Verona, 37134 Verona, Italy, The Microsoft Research-University of Trento Centre for Computational and Systems Biology, 38068 Rovereto, Italy, Department of Computer Science, Wayne State University and Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI 48201, USA
| | - Luca Marchetti
- Barbara Ann Karmanos Cancer Institute and Department of Oncology, Wayne State University, Detroit, MI 48201, USA, Department of Computer Science, University of Verona, 37134 Verona, Italy, The Microsoft Research-University of Trento Centre for Computational and Systems Biology, 38068 Rovereto, Italy, Department of Computer Science, Wayne State University and Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI 48201, USA Barbara Ann Karmanos Cancer Institute and Department of Oncology, Wayne State University, Detroit, MI 48201, USA, Department of Computer Science, University of Verona, 37134 Verona, Italy, The Microsoft Research-University of Trento Centre for Computational and Systems Biology, 38068 Rovereto, Italy, Department of Computer Science, Wayne State University and Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI 48201, USA
| | - Cristina Mitrea
- Barbara Ann Karmanos Cancer Institute and Department of Oncology, Wayne State University, Detroit, MI 48201, USA, Department of Computer Science, University of Verona, 37134 Verona, Italy, The Microsoft Research-University of Trento Centre for Computational and Systems Biology, 38068 Rovereto, Italy, Department of Computer Science, Wayne State University and Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI 48201, USA
| | - Jiusheng Wu
- Barbara Ann Karmanos Cancer Institute and Department of Oncology, Wayne State University, Detroit, MI 48201, USA, Department of Computer Science, University of Verona, 37134 Verona, Italy, The Microsoft Research-University of Trento Centre for Computational and Systems Biology, 38068 Rovereto, Italy, Department of Computer Science, Wayne State University and Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI 48201, USA Barbara Ann Karmanos Cancer Institute and Department of Oncology, Wayne State University, Detroit, MI 48201, USA, Department of Computer Science, University of Verona, 37134 Verona, Italy, The Microsoft Research-University of Trento Centre for Computational and Systems Biology, 38068 Rovereto, Italy, Department of Computer Science, Wayne State University and Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI 48201, USA
| | - Adéle Kruger
- Barbara Ann Karmanos Cancer Institute and Department of Oncology, Wayne State University, Detroit, MI 48201, USA, Department of Computer Science, University of Verona, 37134 Verona, Italy, The Microsoft Research-University of Trento Centre for Computational and Systems Biology, 38068 Rovereto, Italy, Department of Computer Science, Wayne State University and Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI 48201, USA
| | - Vincenzo Manca
- Barbara Ann Karmanos Cancer Institute and Department of Oncology, Wayne State University, Detroit, MI 48201, USA, Department of Computer Science, University of Verona, 37134 Verona, Italy, The Microsoft Research-University of Trento Centre for Computational and Systems Biology, 38068 Rovereto, Italy, Department of Computer Science, Wayne State University and Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI 48201, USA
| | - Sorin Drăghici
- Barbara Ann Karmanos Cancer Institute and Department of Oncology, Wayne State University, Detroit, MI 48201, USA, Department of Computer Science, University of Verona, 37134 Verona, Italy, The Microsoft Research-University of Trento Centre for Computational and Systems Biology, 38068 Rovereto, Italy, Department of Computer Science, Wayne State University and Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI 48201, USA Barbara Ann Karmanos Cancer Institute and Department of Oncology, Wayne State University, Detroit, MI 48201, USA, Department of Computer Science, University of Verona, 37134 Verona, Italy, The Microsoft Research-University of Trento Centre for Computational and Systems Biology, 38068 Rovereto, Italy, Department of Computer Science, Wayne State University and Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI 48201, USA
| |
Collapse
|
3
|
Shekhar MPV, Kato I, Nangia-Makker P, Tait L. Comedo-DCIS is a precursor lesion for basal-like breast carcinoma: identification of a novel p63/Her2/neu expressing subgroup. Oncotarget 2014; 4:231-41. [PMID: 23548208 PMCID: PMC3712569 DOI: 10.18632/oncotarget.818] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
Abstract
Basal breast cancer comprises ~15% of invasive ductal breast cancers, and presents as high-grade lesions with aggressive clinical behavior. Basal breast carcinomas express p63 and cytokeratin 5 (CK5) antigens characteristic of the myoepithelial lineage, and typically lack Her2/neu and hormone receptor expression. However, there is limited data about the precursor lesions from which they emerge. Here we wished to determine whether comedo-ductal carcinoma in situ (comedo- DCIS), a high-risk in situ breast lesion, serve as precursors for basal-like breast cancer. To determine this link, p63, CK5, Her2/neu, epidermal growth factor receptor (EGFR), estrogen receptor (ER) and progesterone receptor (PgR) expression were analyzed by immunohistochemistry in 17 clinical comedo- and 12 noncomedo-DCIS cases, and in tumors derived from unfractionated and CK5-overexpressing subpopulation (MCF10DCIS.com-CK5(high)) of MCF10DCIS.com cells, a model representative of clinical comedo-DCIS. p63 and Her2/neu coexpression was analyzed by immunofluorescence double labeling. A novel p63/CK5/Her2/neu expressing subpopulation of cells that are ER-/PgR-/EGFR- were identified in the myoepithelial and luminal areas of clinical comedo-DCIS and tumors derived from unfractionated MCF10DCIS.com and MCF10DCIS.com-CK5(high) cells. These data suggest that p63 and Her2/neu expressors may share a common precursor intermediate. P63, but not Her2/neu, expression was significantly associated (P = 0.038) with microinvasion/recurrence of clinical comedo-DCIS, and simultaneous expression of p63 and Her2/neu was marginally associated (P = 0.067) with comedo-DCIS. These data suggest that p63/Her2/neu expressing precursor intermediate in comedo-DCIS may provide a cellular basis for emergence of p63+/Her2/neu- or p63+/Her2/neu+ basal-like breast cancer, and that p63/Her2/neu coexpression may serve as biomarkers for identification of this subgroup of basal-like breast cancers.
Collapse
|