Search tips
Search criteria 


Logo of transoncolGuide for AuthorsAbout this journalExplore this journalTranslational Oncology
Transl Oncol. 2010 April; 3(2): 91–98.
Published online 2010 April.
PMCID: PMC2847316

Expression of Long-chain Fatty Acyl-CoA Synthetase 4 in Breast and Prostate Cancers Is Associated with Sex Steroid Hormone Receptor Negativity1


Previous studies have shown that key enzymes involved in lipid metabolic pathways are differentially expressed in normal compared with tumor tissues. However, the precise role played by dysregulated expression of lipid metabolic enzymes and altered lipid homeostasis in carcinogenesis remains to be established. Fatty acid synthase is overexpressed in a variety of cancers, including breast and prostate. The purpose of the present study was to examine the expression patterns of additional lipid metabolic enzymes in human breast and prostate cancers. This was accomplished by analysis of published expression databases, with confirmation by immunoblot assays. Our results indicate that the fatty acid-activating enzyme, long-chain fatty acyl-CoA synthetase 4 (ACSL4), is differentially expressed in human breast cancer as a function of estrogen receptor alpha (ER) status. In 10 separate studies, ACSL4 messenger RNA (mRNA) was overexpressed in ER-negative breast tumors. Of 50 breast cancer cell lines examined, 17 (89%) of 19 ER-positive lines were negative for ACSL4 mRNA expression and 20 (65%) of 31 ER-negative lines expressed ACSL4 mRNA. The inverse relationship between ER expression and ACSL4 expression was also observed for androgen receptor status in both breast and prostate cancers. Furthermore, loss of steroid hormone sensitivity, such as that observed in Raf1-transfected MCF-7 cells and LNCaP-AI cells, was associated with induction of ACSL4 expression. Ablation of ACSL4 expression inMDA-MB-231 breast cancer cells had no effect on cell proliferation; however, sensitivity to the cytotoxic effects of triacsin C was increased three-fold in the cells lacking ACSL4.


A role for altered lipid metabolism in the genesis of the malignant phenotype is suggested by the increased expression of the fatty acid biosynthetic enzymes fatty acid synthase (FASN) and acetyl Co-A carboxylase (ACC) in a variety of tumors, including those that develop in breast and prostate tissues [1,2]. Whereas FASN and ACC are responsible for de novo synthesis of free fatty acids, use of these lipids in subsequent metabolic events, such as glycerolipid synthesis and β-oxidation, requires activation through condensation with a molecule of CoA. There is evidence that activated fatty acids, themselves, can function as transcription factors [3]. The enzymes responsible for the activation reaction comprise a family of proteins known as fatty acyl-CoA synthetases that are classified according to the chain length of their preferred substrates (short, medium, long, and very long). There are five different mammalian isoforms of the long-chain family (ACSL1, 3, 4, 5, and 6), which differ in subcellular localization and substrate specificity [4]. It has been suggested that individual isoforms may serve to channel fatty acids to specific metabolic pathways. ACSL4, for example, is localized to both peroxisomes and mitochondria as a peripheral, rather than integral, membrane protein and has a marked preference for arachidonic and eicosapentaenoic acid as substrates. ACSL4 messenger RNA (mRNA) is highly expressed in placenta, brain, testis, ovary, spleen, and adrenal gland. Relatively low expression levels have been reported in the gastrointestinal tract, including liver, colon, and small intestine [5]. Interestingly, ACSL4 is overexpressed in colon and liver cancer specimens [6,7].Here, we report that this enzyme is overexpressed in estrogen receptor (ER)-negative, androgen receptor (AR)-negative breast tumors and cell lines, and in AR-negative prostate tumors and cell lines. In addition, our studies suggest that expression of ACSL4 is indicative of steroid hormone-independent growth.

Materials and Methods

Cell Lines and Cell Culture

MCF-7, MDA-MB-231, and MDA-MB-415 cells were obtained from American Type Culture Collection (Manassas, VA). T47D cells were a gift from David Kleinberg of this institution; SKBR3 and BT-20 cells were a gift from Herbert Samuels of this institution; and DU145, PC3, LNCaP, and LNCaP-AI cells were previously described [8,9]. Cells were routinely grown at 37°C in a humidified atmosphere in Dulbecco's minimal essential medium (high-glucose) containing Earle's salts and supplemented with 10% fetal bovine serum and antibiotics (penicillin [100 U/ml], Fungizone [0.25 µg/ml], and streptomycin [100 µg/ml]). All cell culture reagents were from Invitrogen (Carlsbad, CA).

Analysis of ACSL4 Protein Expression

Cells were grown in either 96-well or 24-well plates. After a wash with phosphate-buffered saline without calcium or magnesium, either 40 µl (96-well) or 200 µl (24-well) of sample buffer (10 mM Tris- HCl, 1 mM EDTA, 2.5% SDS, 5% β-mercaptoethanol, 0.01% bromophenol blue, pH 8.0) was added to the well. Samples were then heated to 95°C for 5 minutes. Electrophoresis was performed using the PhastGel System from GE Healthcare (Piscataway, NJ). Precast 7.5% acrylamide gels were used with SDS buffer strips. We subjected either 1 or 4 µl of individual samples to electrophoresis. We used Precision Plus protein standards from Bio-Rad (Hercules, CA) as molecular weight markers. After separation, the proteins were transferred to a polyvinylidene fluoride membrane (Hydrabond-P) using the PhastGel transfer apparatus. The membrane was then blocked with 5% milk in phosphate-buffered saline-Tween (0.1%) for 1 hour, followed by an overnight incubation with a 1:2000 dilution of affinity purified rabbit anti-ACSL4 antibody [6]. A 1:5000 dilution of goat antirabbit HRP secondary antibody was used for the final step. Signals were visualized using ECL-Plus chemiluminescence reagent. All immunoblot reagents were from GE Healthcare, with the exception of the antibody to β-actin, which was purchased from Cell Signaling Technologies (Danvers, MA). Quantitation of band densities was accomplished using the Quantity One program from Bio-Rad.

Quantitation of Relative Cell Number

Relative differences in cell number were quantitated using the Cell Titer 96 AQueous Reagent purchased from Promega (Madison, WI). Protocols used were as described by the manufacturer.

Small Interfering RNA-Mediated Knockdown of ACSL4

Cells were plated in T-25 flasks in complete medium lacking antibiotic and allowed to attach overnight. Cell densities at the start of the experiment were between 30% and 60%. Transfection of small interfering RNA (siRNA; either control or ACSL4-specific Smart Pool siRNA purchased from Dharmacon, Lafayette, CO) into cells was accomplished using Lipofectamine RNAiMAX (Invitrogen) according to the protocol recommended by the manufacturer. Transfections were carried out for 48 hours.


Expression data derived from Affymetrix arrays were obtained from the following public databases: Oncomine (, Array Express (, and Gene Expression Omnibus ( The data shown represent the base 2 logarithms of the original values.

Statistical Analyses

A Student's t test (two-tailed) was used to determine significance, unless otherwise noted.


Expression of ACSL4 in Breast Tumor Samples and Cell Lines

A search of the Oncomine database [10] yielded 10 separate studies that reported overexpression of ACSL4 mRNA in human ER-negative breast tumor samples [11–20]. Figure 1A illustrates the results of these studies. For the study by Miller et al. [11], we analyzed the relationship between ER and ACSL4 mRNA expression levels. Figure 1B shows that there is a highly significant inverse correlation between expression levels of ER and ACSL4 mRNA (P < .0001). ACSL1, 5, and 6 were also overexpressed in ER-negative tumor samples, but associated P values were generally 10-fold higher. ACSL3 expression, however, was downregulated in ER-negative tumors compared with ER-positive tumors in four separate studies [14,18,21,22] with P < .001.

Figure 1
Expression of ACSL4 mRNA in human breast tumor samples. (A) Comparison of ASCL4 mRNA levels in ER-negative (solid bars) versus ER-positive human (open bars) breast tumors in ten independent gene expression profile data sets (denoted by study first author). ...

To further investigate the relationship between ACSL4 mRNA levels and ER status, we analyzed microarray expression data reported for 50 human breast cancer cell lines [23]. Figure 2A illustrates results for expression of the five ACSL isoforms in these cell lines as a function of ER status. We found that ACSL4 mRNA expression was significantly higher in ER-negative cells (P < .0001), whereas expression of ACSL3 mRNA was significantly lower (P = .015). We detected no differences in expression of ACSL1, 5, or 6 as a function of ER status. Figure 2B illustrates the range of ACSL4 mRNA expression levels seen in the various cell lines.

Figure 2
Effect of ER status on expression of ACSL4 in human breast cancer cell lines. Data provided by Array Express represents the log to the base 2 of the original data. (A) Expression levels of ACSL mRNA in human breast cancer cells. The expression data for ...

Our next goal was to evaluate whether the observed differences in ACSL4 mRNA expression were recapitulated at the protein level, and whether these putative differences were an exclusive property of ASCL4. To accomplish this, we assessed the levels of ACSL1 and ACSL4 protein relative to those of β-actin, using immunoblot analyses of protein extracts isolated from ER-positive and ER-negative breast cancer cell lines (Figure 2C). We found that all the cell lines expressed detectable levels of ACSL1. These results were consistent with microarray studies that demonstrated expression of ACSL1mRNA in these cell lines (Figure 2A). In addition, we found no correlation between ER status and ACSL1 protein expression levels (Figure 2C), a finding consistent with studies at the mRNA level (Figure 2A). However, with respect to ACSL4, only those cells with normalized mRNA expression values greater than 2.9 appeared positive for ACSL4 by immunoblot analysis (Figure 2C). BT-20 cells had an intensity value of 4.55; MCF-7 cells, 2.52; MDA-MB-231 cells, 5.20; MDA-MB-415 cells, 3.14; SKBR3 cells, 2.77; and T47D cells, 2.62. Using the cutoff for expression indicated by the results from the immunoblot analyses, 17 (89%) of 19 ER-positive cell lines were negative for ACSL4 and 20 (65%) of 31 of ER-negative cells were positive for ACSL4 expression.

AR Status and ACSL4 Expression

A subset of mammary tumors known as molecular apocrine is ER-negative, AR-positive. Analysis of microarray expression data in this subset of breast cancers and in basal (ER-negative, AR-negative) and luminal (ER-positive, AR-positive) breast tumors [24] revealed that ACSL4 mRNA levels were significantly lower in the molecular apocrine samples compared with the basal subset (P < .001, data not shown). Interestingly, of the 11 ER-negative cell lines that do not express ACSL4, 3 showed high levels of expression of AR mRNA. One of these cell lines, MDA-MB-453, has been shown to have a positive proliferative response to androgens [25]. To assess whether expression of ACSL4 and AR were inversely related, we first evaluated results from microarray studies in an ER-negative subset of tumors [14]. Interestingly, we found a significant inverse correlation between AR and ACSL4 mRNA expression levels (Figure 3A) reminiscent of that observed between ER and ACSL4. To explore this issue further, we compared AR and ACSL4 expression levels in prostate cancer cells. First, we analyzed data from a study that assessed mRNA expression in prostate cancer cell lines [26] and found that ACSL4 mRNA was overexpressed in AR-negative cell lines (data not shown). Second, to establish whether the differences in mRNA expression were recapitulated at the protein level, we assessed ACSL4 and β-actin expression in extracts from two AR-negative cell lines (PC3 and DU145), one AR-positive cell line (LNCaP), and one AR-positive cell line that is androgen independent for growth (LNCaP-AI [9]). Figure 3B illustrates the results. We found that both of the AR-negative lines expressed high levels of ACSL4, whereas the AR-positive line did not express the protein. Importantly, we observed that loss of androgen sensitivity in LNCaPAI cells was associated with increased expression of ACSL4, even in the presence of AR (Figure 3B). Finally, we analyzed results from an mRNA expression study in human prostate tumors [27] and found that ACSL4 levels were inversely correlated with AR expression (Figure 3C). These combined data strongly suggest negative links between steroid hormone receptor and ACSL4 expression that could reflect functional relationships in growth requirements or signaling events involving these proteins.

Figure 3
Effect of AR status on expression of ACSL4. (A) Relationship between AR and ACSL4 mRNA expression in 77 ER-negative breast tumor samples as reported in a study by Wang et al. [14]. Data provided by Oncomine. (B) Expression of ACSL4 protein in prostate ...

ACSL4 Expression in MCF-7 Cells Engineered to Overexpress Members of the Mitogen-Activated Protein Kinase (MAPK) Signaling Pathway

Our next goal was to start to identify intermediates that linked steroid hormone receptor and ACSL4 expression. Creighton et al. [28] previously reported that overexpression of key members of the mitogen activated protein kinase (MAPK) signaling pathway in MCF-7 cells results in a molecular fingerprint characteristic of ER-negative human breast tumors. Our studies showed that MCF-7 cells, which express ER and are estrogen-dependent with respect to growth, express ACSL1 but do not express ACSL4 (Figure 2C).We hypothesized that genetic manipulation of MCF-7 cells leading to the expression of the ER-negative phenotype may also result in altered ACSL4 expression. To test this, we analyzed public microarray expression data sets from MCF-7 cells genetically manipulated to activate signaling through MAPK (Figure 4). We focused our attention on the expression of two genes, ESR1 (probe 205225_at) and ACSL4 (probe 202422_s_at), and found that transfection with constitutively active Raf-1 caused induction of ACSL4 (P = .0009; Figure 4). Overexpression of Raf-1 was also accompanied by loss of expression of ER mRNA (P < .0001), a finding consistent with a previous study showing loss of ER protein after transfection of MCF-7 cells with Raf-1 [29]. Interestingly, ACSL3 expression was downregulated in Raf-1-overexpressing cells (data nor shown).

Figure 4
Induction of ACSL4 expression in MCF-7 cells constitutively expressing Raf-1. Data provided by Gene Expression Omnibus. C indicates control; EI, long-term E2-independent growth; erbB-2, cells overexpressing constitutively active c-erbB-2; MEK, cells overexpressing ...

Effect of ACSL4 Ablation on MDA-MB-231 Cells

Because the evidence suggested that ACSL4 expression was associated with sex steroid hormone-independent growth, we wondered if ablation of this enzymatic activity would impact the ability of cells to proliferate. Clearly, the activity was not required for proliferation, in general, as evidenced by the ability of cells lacking ACSL4, such as MCF-7 and T47D, to grow quite well without it. A greater-than 95% reduction in ACSL4 protein expression was achieved by treating cells for 48 hours with ACSL4-specific siRNA, as shown in Figure 5A. The knockdown effect persisted for at least 3 days after removal of the transfection medium (data not shown). When proliferation of the knockdown cells was compared with that of control cells, no difference was observed (Figure 5B).

Figure 5
Effect of ablation of ACSL4 expression on proliferation of MDA-MB-231 cells. Cells were treated for 48 hours with either a control or ACSL4-specific siRNA as described in the text. Cells were then harvested and replated in multiwell plastic dishes and ...

The ACSL inhibitor, triacsin C, is specific for inhibition of ACSL1, 3, and 4, with little or no effect on the activities of ACSL5 or 6 [30]. The half-maximal inhibitory concentration values reported for the three sensitive isoforms indicate that ACSL1 is the most sensitive, whereas ACSL4 is the least sensitive. In addition, this reagent has been demonstrated to inhibit proliferation and induce apoptosis in a variety of cancer cells [31].When we compared the effect of triacsin C treatment on MDA-MB-231 control and knockdown cells, the results shown in Figure 5C were obtained. Ablation of cellular ACSL4 resulted in a three-fold increase in triacsin C sensitivity. The half-maximal inhibitory concentration for triacsin C was 1.59 µM for control cells and 0.56 µM for ACSL4 knockdown cells. These data suggest that ACSL4 activity makes a significant contribution to the overall ACSL activity required for growth and survival of cells.

Prognostic Implication of ACSL4 Expression in ER-Negative Tumors

Because the expression of ACSL4 mRNA in ER-negative tumors varies from strong to none, we next investigated whether ACSL4 levels might have potential prognostic value. Using expression data from a study by Wang et al. [14], we correlated the level of expression of ACSL4 (high or low with respect to the median as cut point) with time of distant metastasis-free survival in 77 node-negative patients who did not receive systematic adjuvant therapy. The results of this analysis are shown in Figure 6. There was a significant difference between the groups (P < .05), suggesting that expression of ACSL4 may have prognostic value.

Figure 6
Correlation of ACSL4 mRNA levels with time to distant metastasis in ER-negative tumors. Kaplan-Meier analysis of 77 ER-negative tumors from node-negative patients who did not receive systematic adjuvant therapy. The log-rank test evaluates whether there ...


Altered expression of lipid metabolic enzymes is a feature of a variety of cancers, including those that develop in breast tissues [32–34]. Both FASN and ACC have been shown to be essential for breast cancer cell survival [35], and inhibition of FASN activity has been shown to have potential chemopreventive [36] and therapeutic [37,38] applications. However, the precise role of altered lipid metabolism in the expression of the malignant phenotype has not been extensively studied. The reported increase in FASN activity in cancer cells may reflect high requirements of these proliferating cells for fatty acids; however, it is unclear whether these fatty acids are necessary for glycerolipid biosynthesis, used as an alternative energy source, or both. It has been reported that prostate cancer cells rely on fatty acids as an energy source [39], and several studies have found that blockade of FASN activity inhibits the growth of cancer cells [37]. A relationship between FASN expression and growth regulatory pathways has also been demonstrated [40].

The first step in the use of free fatty acids for either glycerolipid synthesis or β-oxidation is condensation with a molecule of CoA, a reaction that is catalyzed by ACSLs. Thus far, five mammalian ACSLs that differ in subcellular location and substrate specificity have been identified [4]. The precise role of each isoform has not been delineated, but current evidence suggests that ACSL1 functions in hepatic glycerolipid synthesis [41,42], whereas ACSL3 and ACSL5 seem to increase β-oxidation of fatty acids in certain cells [43]. The localization of ACSL4 to peroxisomes suggests that this enzyme may function in fatty acid oxidation [44]. Inhibitor studies indicate that ACSL4 may also be involved in hepatic triacylglycerol synthesis [45]. Deletion of the human ACSL4 gene has been associated with Alport syndrome, elliptocytosis, and mental retardation [46], and a mutated form of ACSL4 has been reported to be associated with X-linked mental retardation [47]. Mice heterozygous for ACSL4 deficiency present with abnormal uteri [48]. These studies indicate essential roles for ACSL4 in normal development and in reproduction.

It was previously shown that ACSL4 is overexpressed in colon and liver cancers [6,49,50], but to our knowledge, no studies in breast cancer have been reported to date. Comprehensive analyses of public expression databases indicated that ACSL4 mRNA expression is elevated in a subset of human breast cancer specimens. In addition, the data show that overexpression of ACSL4 occurs mainly in ER-negative tumors. We made similar observations in human breast cancer cell lines. Indeed, our analyses showed that 17 (89%) of 19 ER-positive cell lines were negative for ACSL4 expression, whereas 20 (65%) of 31 ER-negative lines expressed ACSL4 to varying degrees. Because a previous report indicated that changes in ACSL4 mRNA levels do not always reflect alterations in protein levels [51], we analyzed several breast cancer cell lines for ACSL4 protein expression. Our studies showed robust correlation between ACSL4 mRNA and protein expression, and they validated use of mRNA expression data sets as good indicators of ACSL4 protein expression. Our combined studies strongly suggested that ER status and ACSL4 protein levels were inversely correlated in human breast cancer.

The observation that several of the ER-negative, ACSL4-negative breast cells lines were positive for expression of AR mRNA led us to postulate that ACSL4 expression may also be linked to that of AR. The microarray data available for prostate tumor samples confirmed a negative correlation between ACSL4 expression and AR expression. To further examine this relationship, we analyzed ACSL4 expression in a variety of human prostate cancer cell lines and found that cells expressing AR lacked ACSL4, whereas those lacking AR expressed ACSL4. Interestingly, AR-positive prostate cancer cells that have developed the ability to grow in an androgen-independent fashion (LNCaP-AI) [52] now express ACSL4. Expression of ACSL3, conversely, has been reported to be stimulated by androgen treatment in prostate cancer [53]. Thus, we concluded that expression of ACSL4 was indicative of androgen insensitivity rather than simply absence of AR.

To further examine the relationship between hormone dependence and ACSL4 expression, we analyzed the consequences of loss of estrogen dependence in MCF-7 breast cancer cells. ER-positive MCF-7 cells in which the MAPK growth pathway is constitutively activated by overexpression of Raf-1 [28] have been shown to lose ER expression and exhibit an ER-negative molecular fingerprint. An examination of the microarray data accompanying these experiments indicates that Raf-1 overexpression and loss of ER are accompanied by induction of ACSL4 expression in these MCF-7 cells. Interestingly, constitutive activation of the MAPK pathway through overexpression of other elements of the pathway, such as EGFR or erbB2, did not result in induction of ACSL4 expression. It is important to emphasize that these correlative studies do not necessarily reflect causal functional relationships. However, an attractive possibility is that up-regulation of ACSL4 expression is necessary for hormone-independent growth of breast and/or prostate tumors. Studies along these lines could have important translational implications.

Another contribution of this study is related to our observations suggesting that ACSL4 levels may also have prognostic value. Approximately 10% of ER-positive tumors are unresponsive to hormone therapy, and many attempts have been made to identify a marker of ER sensitivity that complements ER expression data [54]. In general, expression of ER-inducible proteins has been considered a good index of estrogen sensitivity; however, this parameter may not always reflect hormone-dependent cellular growth. It is possible that simultaneous expression of both ER and ACSL4 might predict a lack of response to hormonal therapy, and we are currently undertaking further studies to evaluate this hypothesis.

With respect to ER-negative breast tumors, we found statistically significant differences in the time of distant metastasis-free survival in patient groups segregated based on ACSL4 mRNA expression levels. It is likely that these differences will become even more significant if protein levels are measured so that additional stratification can be made based on positive or negative protein expression status. Additional studies will be required to assess the utility of ACSL4 levels as prognostic biomarkers of breast cancer.

With respect to prostate cancer, it seems clear that the expression of ACSL4 is correlated with hormone-independent growth; however, the majority of prostate cancers are AR-positive, and it has been suggested that failure of a prostate tumor to respond to hormone-ablative therapy is most likely the result of increased sensitivity to androgens, rather than loss of sensitivity [55]. Thus, ACSL4 expression data would be of limited use.

The contribution of ACSL4 activity to the sex steroid receptor-negative phenotype of human breast cancer remains to be determined. There is evidence suggesting that ACSL3 plays a role in the response of prostate cancer to androgens [26,56], and that ACSL5 promotes glioma cell survival under extracellular acidosis conditions [57]. The induction of ACSL4 expression in sex steroid hormone-independent breast cancer cells suggests that this activity plays a role in facilitating hormone-independent growth, but the precise nature of this contribution remains to be determined. Results of knockdown studies presented here indicate that ACSL4 activity does not influence the growth or survival of MDA-MB-231 cells under the conditions used. It is possible that ACSL4 activity provides an advantage to cancer cells grown under more stringent conditions, such as low pH or hypoxia. But that ACSL4 activity plays a role in the lipid metabolism of MDA-MB-231 cells is indicated by the increased sensitivity of the cells to triacsin C after ablation of ACSL4 expression.

In summary, we have presented data that confirm an association between sex steroid hormone expression and ACSL4 expression in human breast and prostate cancer. More specifically, there is some evidence that ACSL4 expression is more closely associated with hormone-independent growth and, as such, may be a useful marker in determining response to hormonal therapy; however, much more work will be needed to validate such a conclusion.


The authors thank Mark Lippman and C. Kent Osborne for helpful discussions.


1This work was supported by grants from the Department of Defense (M.E.M. and P.L.), the Susan G. Komen Foundation (P.L.), and by National Institutes of Health Grant P01-CA73992 (D.M.S.).


1. Menendez JA, Lupu R. Fatty acid synthase and the lipogenic phenotype in cancer pathogenesis. Nat Rev Cancer. 2007;7(10)(2):63–777. [PubMed]
2. Brunet J, Vazquez-Martin A, Colomer R, Graña-Suarez B, Martin-Castillo B, Menendez JA. BRCA1 and acetyl-CoA carboxylase: the metabolic syndrome of breast cancer. Mol Carcinog. 2008;47(2):157–163. [PubMed]
3. Black PN, Fargeman NJ, DiRusso CC. Long-chain acyl-CoA-dependent regulation of gene expression in bacteria, yeast and mammals. J Nutr. 2000;130(2):305s–309s. [PubMed]
4. Coleman RA, Lee DP. Enzymes of triacylglycerol synthesis and their regulation. Prog Lipid Res. 2004;43:134–176. [PubMed]
5. Cao Y, Traer E, Zimmerman GA, McIntyre TM, Prescott SM. Cloning, expression, and chromosomal localization of human long-chain fatty acid-CoA ligase 4 (FACL4) Genomics. 1998;49:327–330. [PubMed]
6. Cao Y, Dave KB, Doan TP, Prescott SM. Fatty acid CoA ligase 4 is up-regulated in colon adenocarcinoma. Cancer Res. 2001;61:8429–8434. [PubMed]
7. Sung YKP, Park MK, Hong SY, Hwang SY, Kwack MH, Kim JC, Kim MK. Regulation of cell growth by fatty acyl-CoA ligase 4 in human hepatocarcinoma cells. Exp Mol Med. 2007;39(4):477–482. [PubMed]
8. Peng Y, Chen F, Melamed J, Chiriboga L, Wei J, Kong X, McLeod M, Li Y, Li CX, Keng A, et al. Distinct nuclear and cytoplasmic functions of androgen receptor cofactor p44 and association with androgen-independent prostate cancer. Proc Natl Acad Sci USA. 2008;105(13):5236–5241. [PubMed]
9. Li Y, Wang L, Zhang M, Melamed J, Liu X, Reiter R, et al. LEF1 in androgen-independent prostate cancer: regulation of androgen receptor expression, prostate cancer growth, and invasion. Cancer Res. 2009;69(8):3332–3338. [PMC free article] [PubMed]
10. Rhodes DR, Yu J, Shanker K, Deshpande N, Varambally R, Ghosh D, et al. Oncomine: a cancer microarray database and integrated data-mining platform. Neoplasia. 2004;6:1–6. [PMC free article] [PubMed]
11. Miller LD, Smeds J, George J, Vega VB, Vergara L, Ploner A, et al. From the cover: an expression signature for p53 status in human breast cancer predicts mutation status, transcriptional effects, and patient survival. Proc Natl Acad Sci USA. 2005;102(38):13550–13555. [PubMed]
12. Ivshina AV, George J, Senko O, Mow B, Putti TC, Smeds J, et al. Genetic reclassification of histologic grade delineates new clinical subtypes of breast cancer. Cancer Res. 2006;66(21):10292–10301. [PubMed]
13. van de Vijver MJ, He YD, van't Veer LJ, Dai H, Hart AAM, Voskuil DW. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med. 2002;347(25):1999–2009. [PubMed]
14. Wang Y, Klijn JGM, Zhang Y, Sieuwerts AM, Look MP, Yang F, et al. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet. 2005;365(9460):671–679. [PubMed]
15. Minn AJ, Gupta GP, Siegel PM, Bos PD, Shu W, Giri DD, et al. Genes that mediate breast cancer metastasis to lung. Nature. 2005;436(7050):518–524. [PMC free article] [PubMed]
16. Sotiriou C, Wirapati P, Loi S, Harris A, Fox S, Smeds J, et al. Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst. 2006;98(4):262–272. [PubMed]
17. Yu K, Ganesan K, Miller LD, Tan P. A modular analysis of breast cancer reveals a novel low-grade molecular signature in estrogen receptor-positive tumors. Clin Cancer Res. 2006;12(11):3288–3296. [PubMed]
18. Chin K, DeVries S, Fridlyand J, Spellman PT, Roydasgupta R, Kuo W-L, et al. Genomic and transcriptional aberrations linked to breast cancer pathophysiologies. Cancer Cell. 2006;10(6):529–541. [PubMed]
19. Saal LH, Johansson P, Holm K, Gruvberger-Saal SK, She Q-B, Maurer M, et al. Poor prognosis in carcinoma is associated with a gene expression signature of aberrant PTEN tumor suppressor pathway activity. Proc Natl Acad Sci USA. 2007;104(18):7564–7569. [PubMed]
20. Bittner M. Expression Project for Oncology (expO) National Center for Biotechnology Information. 2005. Available at:
21. Ginestier C, Cervera N, Finetti P, Esteyries S, Esterni B, Adelaide J, et al. Prognosis and gene expression profiling of 20q13-amplified breast cancers. Clin Cancer Res. 2006;12(15):4533–4544. [PubMed]
22. Hess KR, Anderson K, Symmans WF, Valero V, Ibrahim N, Mejia JA, et al. Pharmacogenomic predictor of sensitivity to preoperative chemotherapy with paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide in breast cancer. J Clin Oncol. 2006;24(26):4236–4244. [PubMed]
23. Neve RM, Chin K, Fridlyand J, Yeh J, Baehner FL, Fevr T, et al. A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. Cancer Cell. 2006;10(6):515–527. [PMC free article] [PubMed]
24. Farmer P, Bonnefoi H, Becette V, Tubiana-Hulin M, Fumoleau P, Larsimont D, et al. Identification of molecular apocrine breast tumours by microarray analysis. Oncogene. 2005;24(29):4660–4671. [PubMed]
25. Doane AS, Danso M, Lal P, Donaton M, Zhang L, Hudis C, et al. An estrogen receptor-negative breast cancer subset characterized by a hormonally regulated transcriptional program and response to androgen. Oncogene. 2006;25(28):3994–4008. [PubMed]
26. Zhao H, Kim Y, Wang P, Lapointe J, Tibshirani R, Pollack JR, et al. Genome-wide characterization of gene expression variations and DNA copy number changes in prostate cancer cell lines. Prostate. 2005;63(2):187–197. [PubMed]
27. Holzbeierlein J, Lal P, LaTulippe E, Smith A, Satagopan J, Zhang L, et al. Gene expression analysis of human prostate carcinoma during hormonal therapy identifies androgen-responsive genes and mechanisms of therapy resistance. Am J Pathol. 2004;164(1):217–227. [PubMed]
28. Creighton CJ, Hilger AM, Murthy S, Rae JM, Chinnaiyan AM, El-Ashry D. Activation of mitogen-activated protein kinase in estrogen receptor {alpha}-positive breast cancer cells in vitro induces an in vivo molecular phenotype of estrogen receptor {alpha}-negative human breast tumors. Cancer Res. 2006;66(7):3903–3911. [PubMed]
29. Oh AS, Lorant LA, Holloway JN, Miller DL, Kern FG, El-Ashry D. Hyperactivation of MAPK induces loss of ER{alpha} expression in breast cancer cells. Mol Endocrinol. 2001;15(8):1344–1359. [PubMed]
30. Van Horn CG, Caviglia JM, Li LO, Wang S, Granger DA, Coleman RA. Characterization of recombinant long-chain rat acyl-CoA synthetase isoforms 3 and 6: identification of a novel variant of isoform 6. Biochemistry. 2005;44(5):1635–1642. [PubMed]
31. Mashima T, Sato S, Okabe S, Miyata S, Matsuura M, Sugimoto Y, et al. Acyl-CoA synthetase as a cancer survival factor: its inhibition enhances the efficacy of etoposide. Cancer Sci. 2009;100:1556–1562. [PubMed]
32. Kuhajda FP. Fatty acid synthase and cancer: new application of an old pathway. Cancer Res. 2006;66(12):5977–5980. [PubMed]
33. Swinnen JVB, Brusselmans K, Verhoeven G. Increased lipogenesis in cancer cells: new players, novel targets. Curr Opin Clin Nutr Metab Care. 2006;9:358–365. [PubMed]
34. Milgraum LZ, Witters LA, Pasternack GR, Kuhajda FP. Enzymes of the fatty acid synthesis pathway are highly expressed in in situ breast carcinoma. Clin Cancer Res. 1997;3(11):2115–2120. [PubMed]
35. Chajes V, Cambot M, Moreau K, Lenoir GM, Joulin V. Acetyl-CoA carboxylase {alpha} is essential to breast cancer cell survival. Cancer Res. 2006;66(10):5287–5294. [PubMed]
36. Alli PM, Pinn ML, Jaffee EM, McFadden JM, Kuhajda FP. Fatty acid synthase inhibitors are chemopreventive for mammary cancer in neu-N transgenic mice. Oncogene. 2004;24(1):39–46. [PubMed]
37. Lupu R, Menendez JA. Targeting fatty acid synthase in breast and endometrial cancer: an alternative to selective estrogen receptor modulators? Endocrinology. 2006;147(9):4056–4066. [PubMed]
38. Menendez JV, Vellon L, Colomer R, Lupu R. Pharmacological and small interference RNA-mediated inhibition of breast cancer-associated fatty acid synthase (oncogenic antigen-519) synergistically enhances Taxol (paclitaxel)-induced cytotoxicity. Int J Cancer. 2005;115(1):19–35. [PubMed]
39. Liu Y. Fatty acid oxidation is a dominant bioenergetic pathway in prostate cancer. Prostate Cancer Prostatic Dis. 2006;9(3):230–234. [PubMed]
40. Vazquez-Martin A, Colomer R, Brunet J, Lupu R, Menendez JA. Overexpression of fatty acid synthase gene activates HER1/HER2 tyrosine kinase receptors in human breast epithelial cells. Cell Prolif. 2008;41(1):59–85. [PubMed]
41. Li LO, Mashek DG, An J, Doughman SD, Newgard CB, Coleman RA. Overexpression of rat long chain acyl-CoA synthetase 1 alters fatty acid metabolism in rat primary hepatocytes. J Biol Chem. 2006;281(48):37246–37255. [PubMed]
42. Parkes HA, Preston E, Wilks D, Ballesteros M, Carpenter L, Wood L, et al. Overexpression of acyl-CoA synthetase-1 increases lipid deposition in hepatic (HepG2) cells and rodent liver in vivo. Am J Physiol Endocrinol Metab. 2006;291(4):E737–E744. [PubMed]
43. Zhou Y, Abidi P, Kim A, Chen W, Huang T-T, Kraemer FB, et al. Transcriptional activation of hepatic ACSL3 and ACSL5 by oncostatin M reduces hypertriglyceridemia through enhanced {beta}-oxidation. Arterioscler Thromb Vasc Biol. 2007;27(10):2198–2205. [PubMed]
44. Lewin TMVH, Van Horn CG, Krisans SK, Coleman RA. Rat liver acyl-CoA synthetase 4 is a peripheral-membrane protein located in two distinct subcellular organelles, peroxisomes, and mitochondrial-associated membrane. Arch Biochem Biophys. 2002;404:263–270. [PubMed]
45. Kim J-H, Lewin TM, Coleman RA. Expression and characterization of recombinant rat acyl-CoA synthetases 1, 4, and 5. Selective inhibition by triacsin C and thiazolidinediones. J Biol Chem. 2001;276(27):24667–24673. [PubMed]
46. Piccini M, Vitelli F, Bruttini M, Pober BR, Jonsson JJ, Villanova M, et al. FACL4, a new gene encoding long-chain acyl-CoA synthetase 4, is deleted in a family with Alport syndrome, elliptocytosis, and mental retardation. Genomics. 1998;47:350–358. [PubMed]
47. Meloni I, Muscettola M, Raynaud M, Longo I, Bruttini M, Moizard MP, et al. FACL4, encoding fatty acid-CoA ligase 4, is mutated in nonspecific X-linked mental retardation. Nat Genet. 2002;30:436–440. [PubMed]
48. Cho YY, Kang MJ, Sone H, Suzuki T, Abe M, Igarashi M, et al. Abnormal uterus with polycysts, accumulation of uterine prostaglandins, and reduced fertility in mice heterozygous for acyl-CoA synthetase 4 deficiency. Biochem Biophys Res Commun. 2001;284:993–997. [PubMed]
49. Liang YC, Wu CH, Chu JS, Wang CK, Hung LF, Wang YJ, et al. Involvement of fatty acid-CoA ligase 4 in hepatocellular carcinoma growth: roles of cyclic AMP and p38 mitogen-activated protein kinase. World J Gastroenterol. 2005;11:2557–2563. [PubMed]
50. Sung KY, Hwang SY, Park MK, Bae HI, Kim WH, Kim JC, et al. Fatty acid-CoA ligase 4 is overexpressed in human hepatocellular carcinoma. Cancer Sci. 2003;94:421–424. [PubMed]
51. Mashek DGL, Li LO, Coleman RA. Rat long-chain acyl-CoA synthetase mRNA, protein, and activity vary in tissue distribution and response to diet. J Lipid Res. 2006;47:2004–2010. [PubMed]
52. Lu S, Tsai SY, Tsai M-J. Molecular mechanisms of androgen-independent growth of human prostate cancer LNCaP-AI cells. Endocrinology. 1999;140(11):5054–5059. [PubMed]
53. Attard G, Clark J, Ambroisine L, Mills IG, Fisher G, Flohr P, et al. Heterogeneity and clinical significance of ETV1 translocations in human prostate cancer. Br J Cancer. 2008;99:314–320. [PMC free article] [PubMed]
54. Yu JY, Yu J, Cordero KE, Johnson MD, Ghosh D, Rae JM, Chinnaiyan AM, Lippman ME. A transcriptional fingerprint of estrogen in human breast cancer predicts patient survival. Neoplasia. 2008;10(1):79–88. [PMC free article] [PubMed]
55. Kasper S, Cookson MS. Mechanisms leading to the development of hormone-resistant prostate cancer. Urol Clin North Am. 2006;33(2):201–210. [PubMed]
56. Hendriksen PJM, Dits NFJ, Kokame K, Veldhoven A, van Weerden WM, Bangma CH, et al. Evolution of the androgen receptor pathway during progression of prostate cancer. Cancer Res. 2006;66(10):5012–5020. [PubMed]
57. Mashima T, Sato S, Sugimoto Y, Tsuruo T, Seimiya H. Promotion of glioma cell survival by acyl-CoA synthetase 5 under extracellular acidosis conditions. Oncogene. 2008;28:9–19. [PubMed]

Articles from Translational Oncology are provided here courtesy of Neoplasia Press