s2fieldsofstudy: Biology Medicine Chemistry

text:
CDP138 silencing inhibits TGF-β/Smad signaling to impair radioresistance and metastasis via GDF15 in lung cancer

CDP138, a CDK5 binding partner, regulates cell proliferation and migration. However, the mechanisms by which CDP138 functions in these processes remain unclear. In this study, we show that CDP138 is frequently overexpressed and that high levels of CDP138 are correlated with lymph node metastasis in lung cancer. Furthermore, we provide evidence that CDP138-depleted lung cancer cells exhibit enhanced radiosensitivity as well as reduced migration and invasion. Mechanistically, we identify GDF15, a member of the TGF-β superfamily, as a key downstream effector of CDP138. CDP138 silencing attenuates TGF-β/Smad signaling activation at least in part through the downregulation of GDF15. More importantly, the observed phenotypes caused by CDP138 knockdown are partially dependent on GDF15 inhibition. Together, our findings demonstrate that CDP138 positively modulates the TGF-β/Smad signaling pathway via GDF15 to promote radioresistance and metastasis, suggesting CDP138 as a potential oncogenic biomarker and a promising therapeutic target in the treatment of lung cancer.

Lung cancer is the most common malignancy and the leading cause of cancer death worldwide. 1,2 To date, surgery, radiochemotherapy and personalized targeted therapy remain the main treatment for this type of cancer. 3 However, radioresistance and distant metastasis are considered critical causes of the failure to cure cancer. Therefore, intense efforts are needed to better understand the oncogenesis of lung cancer and to identify novel therapeutic targets.
Transforming growth factor (TGF)-β is a key player in the regulation of cellular proliferation, differentiation, motility, invasion, apoptosis and immune responses. [4][5][6] Smad proteins are the intracellular effectors of TGF-β signals. Once phosphorylated, Smad proteins become activate and translocate to the nucleus, ultimately inducing the transcriptional activation of downstream target genes. [7][8][9] To date, numerous studies have demonstrated that aberrant TGF-β/Smad signaling is involved in tumor metastasis, epithelial-mesenchymal transition (EMT) and DNA damage response. [10][11][12] For example, Smad2 and Smad7 have been reported to participate in DNA damage response in an ataxia-telangiectasia mutated (ATM)-dependent manner. Inhibition of TGF-β signaling was found to enhance radiosensitivity in glioblastoma, breast cancer and lung cancer. [13][14][15][16] Moreover, the involvement of Smad2 in EMT through the increase in Snail expression has also been documented. 17 The above findings support the notion that TGF-β/Smad signaling has a pivotal role in tumorigenesis.
C2 domain-containing phosphoprotein (CDP138), also known as KIAA0528, has been reported to be a substrate for Akt2, and it is involved in the regulation of GLUT4 vesicleplasma membrane fusion in response to insulin. 18 In contrast, another study demonstrated that CDP138 is not involved in GLUT4 translocation. 19 Our previous study has shown that CDP138 is a CDK5-and FIBP-interacting protein, and these three molecules can form a stable complex that is involved in cell proliferation and migration. 20 However, the clinical significance and mechanism by which CDP138 participates in these processes remain poorly understood.
In this study, we show that CDP138 protein levels are frequently upregulated and that elevated expression of CDP138 is correlated with lymph node metastasis in lung cancer. Furthermore, CDP138 silencing impairs radioresistance and metastasis in lung cancer cells. More importantly, we demonstrate for the first time that growth differentiation factor 15 (GDF15) acts as a downstream mediator of CDP138induced TGF-β/Smad signaling activation and mediates the biological effects of CDP138 in lung cancer cells.

Results
CDP138 protein level is upregulated in lung cancer cell lines and tissues and is related to lymph node metastasis. We previously showed that knocking down CDP138 suppresses cell growth in breast cancer, 20 implying that CDP138 can act as an oncogenic protein. To investigate the expression of CDP138 in human lung cancer, we first analyzed CDP138 protein level in five human lung cancer cell lines (H1299, HCC827, H292, A549 and H1975) and found it to be significantly higher than that in the normal human bronchial epithelial cell line HBE (Figures 1a and b). Next, we performed immunohistochemical (IHC) analysis of CDP138 expression in a human lung cancer tissue microarray, containing 88 carcinoma tissues and paired paracarcinoma tissues. As shown in Figures 1c and d, CDP138 was primarily located in the cytoplasm and was highly expressed in lung cancer tissues. CDP138 positivity was significantly higher in lung cancer tissues (90.9%) than that in adjacent para-carcinoma tissues (26.1%) (Po0.001). Furthermore, there was a significant correlation between CDP138 expression and lymph node metastasis (Po0.05) ( Table 1). However, there was no significant correlation between CDP138 expression and overall survival in lung cancer patients as determined using the Kaplan-Meier survival analysis (data not shown).
CDP138 silencing impairs proliferation and enhances radiosensitivity in lung cancer cells. Given that CDP138 is frequently overexpressed in lung cancer tissues, we speculated that it may promote tumorigenesis in lung cancer. To this end, we first downregulated the expression of CDP138 in two different lung cancer cell lines (H1299 and HCC827) using siRNAs or shRNAs. As shown in Figure 2a, CDP138 were successfully knocked down. Moreover, CDP138 silencing dramatically suppressed the proliferation of lung cancer cells compared with that of control cells (Figure 2b). The colony formation capability of the cells was also impaired when CDP138 was knocked down (Figure 2c). Therefore, CDP138 promotes the proliferation of lung cancer cells.  After determining the role of CDP138 in a physiological setting, we also wanted to know whether CDP138 is required for the same cellular processes under conditions of stress, such as irradiation (IR)-induced DNA damage. As expected, the loss of CDP138 significantly enhanced cellular sensitivity to radiation (Figure 2d), suggesting that CDP138 has an essential role in promoting radioresistance. To further confirm our hypothesis, γ-H2AX foci formation assay was performed since γ-H2AX is considered a key marker of DNA damage. As shown in Figures 2e and f, the number of γ-H2AX foci was significantly increased in CDP138-depleted lung cancer cells after 4 and 24 h of IR exposure. Together, these data strongly indicate that CDP138 promotes proliferation and radioresistance in lung cancer cells.
Loss of CDP138 suppresses the migration and invasion of lung cancer cells. Our clinical data have clearly shown that CDP138 overexpression is correlated with lymph node metastasis (Table 1). Thus, we speculated that CDP138 may be associated with migration and invasion in lung cancer cells. First, we performed wound healing assay to determine the migratory ability of lung cancer cells. As shown in Figure 3a, CDP138 knockdown cells migrated at a slower rate than the control cells. These phenotypes were further confirmed using transwell assays. As shown in Figures 3b and c, depletion of CDP138 dramatically inhibited cellular migration and invasion. In addition, we found that the overexpression of CDP138 in normal lung epithelial (HBE) cells significantly enhanced their migration and invasion (Figures 3d and e). Thus, CDP138 enhances migration and invasion in lung cancer cells.
CDP138 knockdown attenuates the TGF-β/Smad signaling pathway at least in part via the downregulation of GDF15. To elucidate the underlying mechanisms by which CDP138 Figure 2 CDP138 silencing results in impaired proliferation and enhanced radiosensitivity in lung cancer cells. (a) Western blotting analyses revealed that CDP138 is efficiently knocked down in H1299 and HCC827 cells. (b) Knocking down CDP138 suppresses cell growth. H1299 and HCC827 cells were seeded, and cell numbers were evaluated every day. (c) Colony formation is significantly reduced in CDP138-depleted cells. **Po0.01 and ***Po0.001 compared with controls cells. (d) Radiation sensitivity of H1299 and HCC827 cells lacking CDP138. H1299 cells transfected with indicated siRNAs and stable HCC827 cells were irradiated at indicated doses. Percentages of surviving colonies were examined two weeks later. (e,f) Left panel: H1299 cells (e) or HCC827 cells (f) were exposed to 2 Gy radiation and harvested at indicated time points. Immunostaining was performed to determine γ-H2AX foci formation. Right panel: Quantification of γ-H2AX foci in H1299 cells (e) or HCC827 cells (f). *Po0.05, **Po0.001 compared with controls cells functions in lung cancer, we performed microarray analysis to compare the genomic expression profiles of H1299 cells transfected with control or CDP138-targeting siRNAs. As shown in Figure 4a, there were 14 differentially expressed genes with more than twofold change (six were upregulated, and the rest were downregulated). Among these, we selected four candidate genes (GDF15, DDIT4, SAMD9 and TFPI2) that have been reported to involved in cell proliferation and metastasis [21][22][23][24] (Figure 4b). These candidate genes were further confirmed using quantitative real-time PCR. As shown in Figure 4c, GDF15 was the most downregulated gene in response to CDP138 depletion in lung cancer cells.
Growth differentiation factor 15 (GDF15), also known as macrophage inhibitory cytokine-1 (MIC-1), is a member of the TGF-β superfamily. 21 Western blotting showed that CDP138 knockdown significantly downregulated GDF15 expression in H1299 and HCC827 cells (Figure 4d). Accumulating evidence has shown that GDF15 is involved in the regulation of the TGFβ/Smad signaling pathway. 25,26 Thus, we investigated whether CDP138 is associated with this classical signaling pathway. As shown in Figure 4e, the protein levels of p-Smad2 was reduced in the CDP138-deficient lung cancer cells, whereas the level of total Smad2 remained constant. Importantly, these effects induced by CDP138 knockdown could be partially rescued by GDF15 overexpression (Figure 4f). Therefore, CDP138 silencing attenuates the TGF-β/Smad signaling pathway at least in part via the downregulation of GDF15.
Enhanced radiosensitivity and decreased migration in cells caused by CDP138 knockdown are partially dependent on GDF15 inhibition. To determine whether GDF15 is indeed required for the observed phenotypes induced by CDP138 knockdown in lung cancer cells, the following rescue experiments were performed. First, we transfected exogenously expressed GDF15 to CDP138 knockdown cells ( Figure 5a). As shown in Figures 5b-d, the defects in proliferation and migration induced by CDP138 knockdown in H1299 cells was partially rescued by the overexpression of GDF15. Similarly, restoring GDF15 expression rescued the IR-induced DNA damage response (γ-H2AX foci formation) in CDP138-depleted cells (Figure 5e). To further confirm our  (Figure 6e). This is consistent with GDF15 being a major positive regulator of the TGF-β/Smad signaling pathway. However, CDP138 knockdown had minimal effect on the migration and radioresistance of GDF15-depleted lung cancer cells (Figures 6b-e). Therefore, the enhanced radiosensitivity and reduced migratory ability caused by CDP138 knockdown are partially dependent on GDF15 inhibition.

Discussion
In this study, we find that CDP138 protein is overexpressed and correlated with lymph node metastasis in lung cancer tissues. Furthermore, we show that CDP138 knockdown attenuates the TGF-β/Smad signaling pathway via GDF15, ultimately impairing radioresistance and metastasis in lung cancer. Importantly, GDF15 is identified as a critical downstream mediator of CDP138, indicating that the CDP138/ GDF15/TGF-β pathway is a potential therapeutic target in lung cancer. CDP138 was first identified as an AKT2 downstream substrate required for GLUT4 translocation. 18 Our previous study has demonstrated that CDP138 participates in cell growth and migration in breast cancer. 20 However, little is known about the roles of CDP138 in tumorigenesis, especially in lung cancer. Our results revealed that CDP138 is overexpressed in lung cancer and associated with lymph node metastasis, strongly indicating that CDP138 may be an oncoprotein involved lung cancer metastasis. Further functional studies confirmed this notion and showed that depletion of CDP138 impaired cell proliferation both under physiological conditions and in response to DNA damage and inhibited cell migration and invasion. This finding suggests that CDP138 can contribute to radioresistance and metastasis in lung cancer.
As a member of the TGF-β superfamily, GDF15 has been shown to have important roles in diverse cellular processes such as proliferation, migration, inflammation, metabolism and DNA damage response. 21 Several studies have shown that GDF15 is a radiation-induced biomarker that promotes radioresistance. 27,28 The role of GDF15 in promoting metastasis has also been reported. 29 In addition, GDF15 has been found to be regulated by several critical molecules or signaling pathways. For example, the PI3K/AKT/GSK-3β pathway has been shown to regulate GDF15 expression at both mRNA and protein levels. 30 The transcription factor p53 has also been reported to be required for the induction of GDF15 expression. 31 In our study, we identified GDF15 as a key downstream mediator using microarray analysis. Our results also showed that the expression of GDF15 is regulated by CDP138 at both transcriptional and post-translational levels. Importantly, we found that CDP138 silencing attenuates the TGF-β/Smad signaling pathway partially via GDF15. Therefore, GDF15 likely mediates the biological consequences of CDP138 knockdown in lung cancer cells. Hence, our study identified CDP138 as a novel regulator of the TGF-β/Smad signaling pathway and provided new insights into the mechanisms by which CDP138 functions in the radioresistance and metastasis of lung cancer.
In conclusion, we elucidated the functions of CDP138 in lung cancer and demonstrated that CDP138 affects biological processes mainly via the GDF15-mediated TGF-β/Smad signaling pathway. Given that CDP138 is frequently overexpressed and causes radioresistance and metastasis in lung cancer, it may be a promising therapeutic biomarker for cancer radiotherapy, especially in lung cancers displaying elevated levels of CDP138.

Materials and Methods
Cell cultures. Five human lung cancer cell lines (H1299, HCC827, H292, A549 and H1975) and one normal human bronchial epithelial cell line HBE were purchased from American Type Culture Collection and maintained in RPMI-1640 with 10% fetal bovine serum and 100 μg/ml penicillin and streptomycin at 37°C in 5% CO 2 . TGF-β was purchased from Calbiochem and stored at − 20°C.
Establishment of stable lung cancer cell lines. The shRNA sequences have been previously described. 20 HEK293T cells were transiently transfected with CDP138 shRNAs and packaging plasmids pSPAX2 and pMD2G (kindly provided by Dr Zhou Songyang, Baylor College of Medicine). At 48 h posttransfection, the lentiviral supernatants were filtered and used to infect HCC827 cells in the presence of 8 μg/ml polybrene. Stable cell lines were selected with media containing 2 μg/ml puromycin and confirmed by Western blotting.
Gene expression microarrays. H1299 cells were transfected with control or CDP138-targeting siRNAs using Lipofectamine RNAiMAX for 48 h. Total RNA was isolated using Trizol reagent (Invitrogen) according to the manufacturer's instructions. Microarray experiments were performed using Affymetrix gene chip. Genes were determined to be significantly differentially expressed with a selection threshold of false discovery rate (FDR) waso5% and fold change was 42.0. The 8 most upregulated and 6 most downregulated genes are presented as heat maps.
Quantitative real-time PCR. This assay was performed as previously described. 32 Briefly, total RNA was prepared using Trizol reagent. First-strand cDNA was synthesized using the qPCR RT Master Mix (Toyobo, Osaka, Japan). The relative gene expression levels were calculated using the ΔCt method (Ct of GAPDH minus the Ct of the target genes). Primer sequences are listed in Supplementary Table 1.
Western blotting. Cell lysates were prepared using NETN buffer (20 mM Tris-HCl, pH 8.0, 100 mM NaCl, 1 mM EDTA and 0.5% Nonidet P-40), separated by SDS-PAGE and transferred to PVDF membranes. The lysates were then incubated with primary antibodies against CDP138 (Bethyl Laboratories, Montgomery, TX, USA), GDF15 (Santa Cruz Biotechnology, Santa Cruz, CA, USA), p-Smad2 Cell growth and colony formation assay. Cells were seeded at a density of 1.0 × 10 4 cells/ml in 6-well plates, and cell numbers were evaluated every day. Alternatively, cells were plated in triplicate in six-well plates and irradiated at indicated doses. After being grown two weeks, the cells were Wound healing assay. This assay was performed as previously described. 20 Briefly, confluent cell layers were scratched with 200-μl pipet tips, washed twice with PBS to remove detached cells, and then incubated in serum-free medium. Images were photographed 36 h later with a microscope.
Cell migration and invasion assays. This assay was performed as previously described. 20 Briefly, for migration assays Immunofluorescence staining. Cells were cultured on coverslips and exposed to 2 Gy radiation. The cells were then fixed with 4% paraformaldehyde solution at various time points after IR (30 min, 4 h and 24 h) and permeabilized with 0.2% Triton X-100 for 5 min. After being blocked with 5% bovine serum albumin, the samples were incubated with anti-γ-H2AX antibody overnight at 4°C. The cells were then washed and incubated with secondary antibodies for 1 h. After being counterstained with DAPI, immunostained cells were examined with a fluorescence microscope.
IHC staining. A lung cancer tissue microarray was obtained from Shanghai Outdo Biotech (Shanghai, China), which contained 90 carcinoma tissues and paired para-carcinoma tissues. All patients were pathologically diagnosed with lung adenocarcinoma. IHC analysis was performed as previously described. 33 Briefly, tissue sections were blocked with goat serum after antigen retrieval using citrate buffer. Then, tissue sections were incubated with anti-CDP138 antibody (Bethyl Laboratories) overnight at 4°C. After being incubated with secondary antibody, the tissue sections were washed with PBS, reacted with 3,3-diaminobenzidine and counterstained with haematoxylin. Both the percentage of positive area and staining intensity were recorded to evaluate the expression of CDP138.
Statistical analyses. Each experiment in our study was independently performed at least three times. Unpaired Student's t-test was used for statistical comparison. Differences between variables were assessed using the χ 2 test. The Kaplan-Meier method was used to construct the survival curves. P-valueo0.05 was considered statistically significant.

Conflict of Interest
The authors declare no conflict of interest. with indicated siRNAs were exposed to 2 Gy radiation and harvested at the indicated time points. Immunostaining was performed to examine γ-H2AX foci formation. Lower panel: quantification of γ-H2AX foci in H1299 cells. *Po0.05 and **Po0.01. n.s. indicates no statistically significant difference (P40.05)


extfieldsofstudy: Biology Medicine

text:
8-oxoguanine DNA glycosylase (OGG1) deficiency elicits coordinated changes in lipid and mitochondrial metabolism in muscle

Oxidative stress resulting from endogenous and exogenous sources causes damage to cellular components, including genomic and mitochondrial DNA. Oxidative DNA damage is primarily repaired via the base excision repair pathway that is initiated by DNA glycosylases. 8-oxoguanine DNA glycosylase (OGG1) recognizes and cleaves oxidized and ring-fragmented purines, including 8-oxoguanine, the most commonly formed oxidative DNA lesion. Mice lacking the OGG1 gene product are prone to multiple features of the metabolic syndrome, including high-fat diet-induced obesity, hepatic steatosis, and insulin resistance. Here, we report that OGG1-deficient mice also display skeletal muscle pathologies, including increased muscle lipid deposition and alterations in genes regulating lipid uptake and mitochondrial fission in skeletal muscle. In addition, expression of genes of the TCA cycle and of carbohydrate and lipid metabolism are also significantly altered in muscle of OGG1-deficient mice. These tissue changes are accompanied by marked reductions in markers of muscle function in OGG1-deficient animals, including decreased grip strength and treadmill endurance. Collectively, these data indicate a role for skeletal muscle OGG1 in the maintenance of optimal tissue function.

Introduction
Endogenous metabolic byproducts and exogenous oxidants can cause extensive oxidative damage to both genomic and mitochondrial DNA (mtDNA). Unrepaired oxidative DNA damage can in turn lead to mutagenesis, cellular transformation and dysfunction, and cell death [1][2][3][4]. The cell therefore has multiple mechanisms to guard against DNA damage and to repair existing damage. The primary pathway for repair of non-bulky oxidative lesions is the base-excision repair (BER) pathway that is initiated by DNA glycosylases. These enzymes, including 8-oxoguanine DNA glycosylase (OGG1), Nei endonuclease VIII-like (NEIL)1, NEIL2, NEIL3, and endonuclease III-like 1 (NTH1), have distinct tissue distributions and substrate specificities to recognize and excise specific subsets of lesions, and in some cases, can further process the damaged site to a single-strand break via an intrinsic AP lyase activity [5][6][7].
Skeletal muscle is one of the primary sites of glucose disposal in the body, and pathologies such as insulin resistance and diabetes are thought to be affected by the accumulation of lipids and alterations in the metabolic capacity of skeletal muscle. Since Ogg1 -/mice were previously shown to be prone to insulin resistance, we were interested in determining the effects of OGG1 deficiency on skeletal muscle metabolism and function. In order to avoid the confounding effects of excess body weight and adiposity on muscle function, the studies presented below were carried out in chow-fed animals, prior to the onset of differences in body mass and composition.

Ogg1 -/mice have increased muscle lipid deposition
We have previously shown that mice lacking the BER enzyme OGG1 are prone to obesity and insulin resistance with increasing age or upon high-fat diet (HFD) feeding [28]. Since skeletal muscle is one of the primary sites of glucose disposal in the body, we were interested in determining the effects of OGG1 deletion on skeletal muscle physiology and function. For this study, WT and Ogg1 -/mice were studied under chow-fed conditions at 22 weeks of age, prior to the onset of adiposity in Ogg1 -/animals.
Since increased intramuscular muscle lipid deposition is a known risk factor for impaired insulin signaling [31-33], muscle lipid content was measured in WT and Ogg1 -/animals. Interestingly, Ogg1 -/mice had significantly increased muscle triacylglycerols (TG), cholesterol esters (CE), and diacylglycerols (DAG) (Fig 1A-1C), relative to WT counterparts. Total free fatty acid (FFA) and phospholipid (PL) content were not significantly different between the genotypes (Fig 1D and 1E). In addition to changes in total content, the fatty acid composition of several lipid moieties was also differentially affected by genotype (Tables 1-5). The increases in muscle TG and CE were primarily accounted for by an accumulation of 16 and 18 carbon mono-and polyunsaturated fatty acids, which are the predominant substrates for synthesis of these storage lipids (Tables 1-5). The observed increase in the DAG fraction in Ogg1 -/muscle was primarily due to an increase in oleic acid (18:1 n-9), as well as the polyunsaturated fatty acids arachidonic acid (20:4 n-6) and docosahexanoic acid (22:6 n-3) (Table 3). Interestingly, although total free fatty acid (FFA) levels were not increased in muscle of Ogg1 -/mice, levels of docosahexanoic acid (DHA, 22:6) were significantly higher in the FFA fraction of muscle lipids in these animals, relative to WT counterparts (Table 4). It is notable that this increase in free DHA in Ogg1 -/mice represented an over 20-fold increase over WT levels. Most studies detailing the role of omega-3 fatty acids in skeletal muscle performance are performed under conditions of dietary supplementation with excess omega-3 lipids [34]. In our model, the  Ogg1 -/mice display an increase in DHA without dietary supplementation, possibly due to increased mobilization or altered partitioning of this polyunsaturated fat. The physiological significance of this dramatic increase is not yet understood. Total phospholipid (PL) content was not significantly different between WT and Ogg1 -/mice. However, levels of vaccenic acid (18:1 n-7) and arachidonic acid (20:4) were significantly reduced in PL from Ogg1 -/muscle, relative to WT counterparts (Table 5). This reduction in PL arachidonic acid parallels the increase in this fatty acid species within the DAG pool.
No change in mtDNA content or mitochondrial OXPHOS protein content in Ogg1 -/mice There is considerable disagreement in the field regarding the role of skeletal muscle mitochondrial dysfunction in the development of whole body insulin resistance [35][36][37][38][39][40][41][42][43][44][45][46][47][48]. Since we have previously reported that Ogg1 -/mice have impaired insulin sensitivity [28], and given that OGG1 is involved in repair of both genomic, as well as mtDNA [5,49], we were interested in determining the role of OGG1 deficiency on mitochondrial content in the muscle of these animals. There were no differences in total content of mtDNA between genotypes, as measured by qPCR against several different mtDNA target regions (Fig 2A). Additionally, expression of proteins involved in mitochondrial OXPHOS, as well as VDAC, a mitochondrial membrane protein that is indicative of mitochondrial abundance, were not different between genotypes ( Fig 2B). Collectively, these data indicate that OGG1 deficiency does not result in altered mitochondrial content in skeletal muscle. Therefore, a reduction in mitochondrial content is not likely to be a contributor to insulin resistance in the Ogg1 -/model.
No alterations in DNA damage markers in skeletal muscle of Ogg1 -/mice mtDNA integrity was assessed by long-amplicon PCR, as previously described [50,51]. Amplification of a 10 kb mtDNA fragment before and after FPG treatment was normalized against amplification of a short mtDNA fragment. Differences in amplification before and after FPG treatment were interpreted to indicate sites of oxidatively modified bases. Using this assay, there were no measurable differences in mtDNA amplification between WT and Ogg1 -/mice in skeletal muscle DNA ( Fig 3A). These results are consistent with previous reports suggesting tissue-specific differences in accumulation and repair of oxidative DNA damage [9,52,53]. The lack of difference between WT and Ogg1 -/mice is also supportive of the existence of backup repair mechanisms or alternative methods of dilution or elimination of mtDNA damage in skeletal muscle [9,54,55]. Interestingly, using this method, we observed a 75% reduction in amplification of mtDNA in both genotypes, upon FPG treatment. These data suggest that endogenous levels of oxidative lesions in post-mitotic tissues such as skeletal muscle may be rather high. Content of 8-oxoG in total DNA (nuclear and mtDNA) was measured using a commercially available ELISA. Total 8-oxoG content was not significantly different between WT and Ogg1 -/mice (Fig 3B), Table 3. Muscle diacylglycerol (DAG) composition. Fatty acid composition of diacylglycerol from gastrocnemius of WT and Ogg1 -/mice was analyzed by gas chromatography. Data are averages of 6 animals per genotype and are presented as average nmol fatty acid per g of wet weight. Data are expressed as mean ± SEM; *p<0.05 vs. WT.

Altered mitochondrial fission in Ogg1 -/mice
Mitochondrial function is known to be affected not only by mitochondrial content, but also by mitochondrial morphology, which is maintained through constant fission and fusion processes [56][57][58]. We therefore measured two key markers of mitochondrial fission in muscle, Drp1 and Fis1. Gene expression, as well as protein levels of these mediators of mitochondrial fission were both significantly increased in muscle of Ogg1 -/mice, relative to WT counterparts ( Fig 2C and 2D). These changes are consistent with previous reports regarding increased muscle mitochondrial fission being observed in obese and insulin-resistant muscle. However, it is notable that in Ogg1 -/mice, these increases in markers of mitochondrial fission precede the development of obesity or insulin resistance, and may therefore be involved in the etiology of metabolic aberrations observed in these mice. Although the mechanisms leading to these changes in gene expression are not clear, some possible mechanisms are presented in the Discussion.

Increased expression of lipid uptake genes in muscle of Ogg1 -/mice
We have previously reported that genes regulating fatty acid oxidation (FAO) are significantly downregulated in livers of HFD-fed Ogg1 -/mice, accompanied by increased hepatic lipid accumulation upon HFD-feeding [28]. To determine if the increased lipid deposition in skeletal muscle was accompanied by alterations in lipid oxidation, expression of key FAO genes was measured by qRT-PCR. Interestingly, Ogg1 -/mice had increased expression of FAO genes (Fig 4A), relative to WT counterparts. Thus, the increased lipid deposition in muscle of chow-fed Ogg1 -/mice is not likely to be a consequence of reduced fat oxidation. Levels of muscle lipids can be modulated not only by oxidation of fatty acids, but also by regulation of lipid uptake by fatty acid transporters [59][60][61][62]. Expression of the two key fatty acid transporters, fatty acid translocase (FAT/CD36) and fatty acid transport protein 1 (FATP1) was significantly upregulated in Ogg1 -/mice, relative to WT counterparts (Fig 4B), commensurate with the increased muscle lipid deposition observed in these animals.
Altered regulation of pyruvate metabolism and TCA cycle genes in Ogg1 -/muscle Since fatty acid uptake and oxidation genes were upregulated in Ogg1 -/mice, we hypothesized that genes regulating TCA cycle flux may be differentially expressed in the muscle of these animals. Indeed, several key genes of the TCA cycle including malate dehydrogenase 1(Mdh1), isocitrate dehydrogenase 3a (Idh3a), and fumarate hydratase (Fh1) were significantly upregulated in Ogg1 -/mice, relative to WT counterparts ( Fig 4C). Conversely, expression of genes regulating synthesis and entry of the glycolytic endpoint, pyruvate, into the TCA cycle was significantly reduced in muscle of Ogg1 -/mice. This included genes encoding muscle pyruvate kinase (M-Pk), which catalyzes the final step of glycolysis converting phosphoenolpyruvate to pyruvate; pyruvate carboxylase (Pc), which allows for entry of pyruvate into the TCA cycle via its conversion to oxaloacetate; and pyruvate dehydrogenase (Pdh), which catalyzes the conversion of pyruvate to acetyl-CoA as a substrate for the TCA cycle. These data collectively suggest that OGG1 deficiency results in altered skeletal muscle substrate metabolism, potentially favoring fat oxidation for meeting energy needs in muscle.

Altered muscle function in Ogg1 -/mice
To determine if these alterations in muscle carbohydrate and lipid metabolism translated to changes in muscle function, muscle grip strength and endurance were measured. Grip strength across all four limbs was significantly reduced in Ogg1 -/mice, relative to WT counterparts ( Fig 5A). In addition, when placed on a treadmill, Ogg1 -/mice had significantly reduced times to exhaustion, when compared to WT counterparts, indicating decreased endurance in these animals ( Fig 5B). Furthermore, we have previously reported that Ogg1 -/mice have significantly reduced glucose tolerance [28]. Given that skeletal muscle is the primary site of glucose disposal, these data indicating reduced grip strength and endurance add to the evidence that OGG1 expression in skeletal muscle is essential for maintaining optimal muscle function.

Discussion
We demonstrate here that OGG1 activity in skeletal muscle is an important determinant of muscle function and metabolism. Targeted deletion of this critical DNA repair enzyme results in marked alterations in skeletal muscle metabolism, favoring fat uptake and accumulation (Figs 1 and 5). We have shown previously that when placed on a HFD, Ogg1 -/mice proceed to develop severe insulin resistance and other features of the metabolic syndrome, including fatty liver [28]. Interestingly, the changes in lipid metabolism and tissue function of skeletal muscle described herein precede the development of obesity or insulin resistance. They may therefore offer important insights into the etiology of metabolic disease in this model of oxidative stressinduced damage. It is notable that a recent study demonstrated that in a model of mitochondrial overexpression of OGG1, muscle myotubes were resistant to the lipotoxic effects of saturated fatty acids on insulin signaling [63], suggesting an important role for mitochondrial OGG1 in regulating metabolic health. While this may be the case in a model of OGG1 overexpression, the results of our mtDNA amplification assay (Fig 3A) suggest that under chow-fed basal conditions, there are no measurable differences between WT and Ogg1 -/mice in the accumulation of FPG-sensitive lesions (primarily oxidized guanines) in muscle mtDNA. It was also notable that under chow-fed conditions, we observed no differences in total 8-oxoG content in skeletal muscle of Ogg1 -/mice ( Fig 3B). It is therefore plausible that the observed

8-oxoG as an epigenetic mark
Mechanistically, the mode of regulation of metabolic genes and genes of mitochondrial fission by OGG1 deficiency is not yet known. 8-oxoG in promoter regions of transcribed genes has been suggested to act as an epigenetic mark (rev. in [68]). For instance, binding of OGG1 to oxidized guanines in nuclear DNA has been shown to promote binding of transcription factors such as NFkB [66,67,69] and HIF1α [70]. This is notable since both Drp1 and Fis1 have been  shown to be transcriptionally activated under conditions of HIF-1α activation [71]. In addition to the recruitment of transcription factors, OGG1 has been shown to participate in transcription initiation of estrogen-responsive genes, in which it is recruited through localized oxidative bursts stemming from active DNA demethylation at promoter sites [72]. Moreover, it has been recently reported that OGG1 recruits the DNA demethylase TET1 to sites of oxidative lesions, promoting DNA demethylation [73]. It is therefore possible that alterations in epigenetic marks, such as DNA methylation, may drive some of the gene expression changes observed in skeletal muscle of Ogg1 -/mice.

Linking OGG1 status to mitochondrial dynamics
Ogg1 -/mice have significant alterations in markers of mitochondrial fission such that key genes and proteins regulating fission are significantly upregulated (Fig 2). Similarly, Torres-Gonzalez et al. recently reported that in a cultured cardiomyocyte model exposed to acute oxidative stress, adenoviral OGG1 overexpression resulted in reduced expression of DRP1 and FIS1 and decreased mitochondrial fragmentation [74], supporting the conclusion that OGG1 status is linked to regulation of mitochondrial dynamics in both in vivo and in vitro models. These data are especially interesting in light of a recent report suggesting that increased mitochondrial fission mechanistically contributes to the induction of insulin resistance in skeletal muscle [75]. This report by Jheng et al. demonstrated significant increases in muscle mitochondrial fission in models of obesity. However, the causal mechanisms leading to this increase were not determined. In our model, the temporality of increased mitochondrial fission occurring prior to changes in body weight offers potentially important insights into the regulation of insulin sensitivity by mitochondrial fission. In the absence of efficient oxidative DNA repair, Ogg1 -/mice have increased mitochondrial fission markers and subsequently go on to develop insulin resistance. This sequence of events is suggestive of OGG1 status being a determinant of mitochondrial dynamics. In this regard, it has been previously suggested that plasticity in mitochondrial dynamics may be a cellular tolerance mechanism for unrepaired damage. For instance, UV-induced helix-distorting lesions in mtDNA, which are not otherwise repaired through mitochondrial repair pathways, were shown to be tolerated via induction of both fission and fusion processes in a C. elegans model [76]. Although we did not observe any differences in static levels of oxidized lesions in mtDNA, as measured by the long-amplicon PCR method (Fig 3), it is possible that the increase in mitochondrial fission in Ogg1 -/muscle (Fig 2C and  2D) serves to dilute damage as it is generated. Ongoing studies are designed to determine the consequences of pharmacological inhibition of mitochondrial fission in the context of OGG1 deficiency.

Skeletal muscle lipid handling
In addition to these novel findings of altered mitochondrial fission, we also describe several changes in lipid content and composition in muscle of Ogg1 -/mice. While it is known that high-fat feeding induces muscle lipid accumulation, it is interesting to note that OGG1 deficiency alone, even in the absence of a HFD, results in significant lipid accumulation in skeletal muscle (Fig 1). This increase in intramuscular lipids is accompanied by a significant increase in genes regulating fatty acid import into muscle cells (Fig 4). Muscle substrate utilization is primarily controlled by the availability of substrates. Under conditions of increased fatty acid availability, muscle fat uptake and oxidation is increased, while glucose oxidation is reduced. Conversely, under conditions of excess glucose, glucose oxidation is increased with lipid uptake and oxidation being reduced.
We previously reported that although lipid oxidation was reduced in livers of chow-fed Ogg1 -/mice, there was no significant hepatic lipid accumulation under chow-fed conditions in these animals [28]. These data regarding muscle fatty acid handling therefore indicate that under chow-fed conditions, excess lipids may be channeled to skeletal muscle for utilization and storage. The increase in genes regulating both uptake and oxidation of fatty acids in muscle of chow-fed Ogg1 -/mice may therefore be a consequence of increased lipid availability as a consequence of reduced hepatic lipid oxidation.
The finding of increased markers of fatty acid uptake in skeletal muscle of Ogg1 -/mice is supportive of the idea that skeletal muscle may act as a sink for excess lipids in Ogg1 -/animals, under chow-fed conditions. Given the known correlation between muscle lipid accumulation and insulin resistance, it is possible that this increase in lipids in skeletal muscle of Ogg1 -/mice plays an important role both in modulation of mitochondrial dynamics (Fig 2), as well as in subsequent blunting of insulin sensitivity, as previously reported [28]. Furthermore, it is interesting to note that the reduction in arachidonate (20:4) in the PL fraction of Ogg1 -/muscle is accompanied by an increase in arachidonate in the DAG fraction of these mice (Tables 5 and  3, respectively). The fatty acid composition of DAG has been shown to affect cellular outcomes such as activation of protein kinases, as well as signaling through the MAPK pathway via activation of RAS GTPases [77][78][79]. Given the observed differences in fatty acid composition of lipid moieties in Ogg1 -/muscle, it may therefore be important to determine the role of these alterations in downstream signaling cascades in these mice.
The findings of increased lipid uptake in muscle of Ogg1 -/mice also raise the question of lipid handling in muscle myotubes of OGG1 overexpressing mice. A previous report by Yuzefovych et al. indicated that muscle myotubes from mice overexpressing mitochondrial OGG1 were resistant to the toxic effects of palmitate exposure [63]. The effects of OGG1 overexpression on lipid uptake and metabolism were not determined in that study but would be interesting to measure in light of our results in Ogg1 -/muscle (Fig 4B).

8-oxoguanine DNA glycosylase alters skeletal muscle metabolism
Based on the results of the current study, we propose that the absence of OGG1 alters both lipid metabolism, as well as mitochondrial health in skeletal muscle. While it is not known whether this occurs through OGG1's role in DNA repair or through its described roles in transcription regulation, it ultimately results in compromised muscle function and strength. These findings elucidate a novel pathway of metabolic regulation downstream of OGG1 and suggest an important role for this enzyme and the BER pathway in the maintenance of muscle function.

Animal studies
The generation of Ogg1 -/mice backcrossed 21 times to C57BL/6J background has been previously described. [18,28] At OHSU, the Ogg1 -/allele was maintained through additional backcrossing to C57BL/6J and subsequent matings between Ogg1 +/mice. Age-matched male mice were exclusively used throughout this investigation. 12-week old mice were individually housed and given ad libitum access to rodent chow for 10 weeks prior to euthanasia. At the end of 10 weeks of feeding, mice were euthanized by CO 2 overdose followed by cervical dislocation, and tissues were collected and snap frozen in liquid nitrogen for further analyses. For skeletal muscle experiments, mixed gastrocnemius tissue was used. For in vivo procedures, all efforts were made to minimize discomfort and suffering, in accordance with approved animal care protocols. The breeding and care of animals are in accordance with the protocols approved by the Animal Care and Use Committee of Oregon Health & Science University, Portland, Oregon.

Tissue lipids
Total lipids were extracted from skeletal muscle according to the methods of Bligh and Dyer [80] and analyzed by TLC followed by gas chromatography, as described previously [81].

Grip strength
Grip Strength of all 4 limbs was measured using a Chatillon E-DFE Series Digital Force Gauge. After a period of acclimatization, 7-8 mice of 18-20 weeks of age were analyzed 3 times sequentially, with a 7 minute rest between measurements. Data were recorded as gram/force exerted by the mouse and normalized for body weight.

Treadmill running test
Mice were placed on the belt of a six-lane motorized treadmill (Exer 3/6 Treadmill; Columbus Instruments, Columbus, OH) supplied with shocker plates. The treadmill was run at an incline of 0˚at 5 m/min for 5 min, after which the speed was increased 1 m/min every minute. The test was stopped when the mouse remained on the shocker plate for 20 s without attempting to reengage the treadmill, and the time to exhaustion was determined.

mtDNA amplification assay
The long-amplicon quantitative PCR was performed as described [50,51] with few modifications. First, DNA was treated with FPG (New England Biolabs), which acts as an N-glycosylase and AP-lyase on 8-oxoG and oxidized purines such as 2,6-diamino-4-hydroxy-5-formamidopyrimidine (FapyG), and 4,6-diamino-5-formamidopyrimidine (FapyA) to generate PCRblocking single strand breaks at sites of oxidative damage. Quantitative PCR was then used to determine the content of specific intact sequences. The difference in PCR amplification after 8-oxoguanine DNA glycosylase alters skeletal muscle metabolism FPG cleavage was compared to amplification in uncleaved DNA to estimate oxidative lesion content in mtDNA. Following FPG treatment, DNA was accurately quantified fluorometrically using PicoGreen (Quant-iT™ PicoGreen 1 dsDNA Assay Kit, Invitrogen) and diluted in TE buffer (10 mM Tris-HCl, 1 mM EDTA, pH 8.0) to a final concentration of 3 μg/ml. Two targets of mtDNA were amplified: a long target to quantify levels of mtDNA lesions and a short target to control for changes in mtDNA copy number. The long target (% 10 kbp) spanned the Nd1 and Nd5 genes and the small target (127 bp) was part of Nd1 gene. The primer nucleotide sequences were as follows: 5'-GCC AGC CTG ACC CAT AGC CAT AAT-3' and 5'-GCC GGC TGC GTA TTC TAC GTT A-3' for short target, 5'-GCC AGC CTG ACC CAT AGC CAT AAT-3' and 5'-GAG AGA TTT TAT GGG TGT AAT GCG G-3' for long target. The total volume for each PCR reaction was 20 μl, consisting of 15 ng of DNA template, 1x Platinum™ SuperFi™ PCR Master Mix (Invitrogen), 0.5 μM forward primer and 0.5 μM reverse primer. Samples were run in duplicates. The PCR parameters for the short mitochondrial target were 1 min at 95˚C, then 16 cycles of 30 s at 95˚C, 45 s at 72˚C, followed by a final extension step of 5 min at 72˚C. The parameters for the long mitochondrial target were 1 min at 95˚C, then 15 cycles of 15 s at 95˚C, 10 min at 70˚C, followed by a final extension step of 10 min at 70˚C. The PCR products were then quantified fluorometrically, and the results were expressed as mtDNA long amplicon amplification normalized for short amplicon amplification. Results before and after FPG treatment are shown.

8-oxoG ELISA
Total DNA was isolated from gastrocnemius of WT and Ogg1 -/mice using the QIAamp DNA Mini Kit. Equal amounts of total DNA from each animal were pooled, and 10 μg of DNA was analyzed in duplicate using a commercially available 8-oxoG ELISA kit (Trevigen, Gaithersburg, MD) following manufacturer's protocols. mtDNA quantitation and gene expression analysis mtDNA content was measured by qPCR using primers directed against three different regions of mtDNA corresponding to regions encoding for ATP synthase F o subunit 6 (Atp6), Cytochrome c oxidase subunit 2 (CytoxII), and NADH dehydrogenase 5 (Nd5). Data were normalized for the high-copy number nuclear gene, 18S rRNA. RNA for quantitative real-time PCR (qPCR) was isolated using Tri-reagent RT (MRC, Inc., Cincinnati, OH). 1 μg of RNA was reverse-transcribed using the Superscript III first-strand synthesis system (Invitrogen, Carlsbad, CA). qPCR was performed on a Bio-Rad iCycler qPCR instrument (Bio-Rad, Hercules, CA) using gene-specific primers. Gene expression was normalized to expression of 18S rRNA. Primer sequences are available upon request.

Mitochondrial protein content
A total of 50 μg of mitochondrial proteins or whole cell lysates were resolved by SDS-PAGE followed by immunoblotting with antibodies against proteins of the mitochondrial oxidative phosphorylation (OXPHOS) complex and the voltage dependent anion channel (VDAC) (both from Mitosciences, Eugene, OR) or antibodies against mitochondrial fission 1 protein (FIS1) (Pierce, Waltham, MA), dynamin related protein 1 (DRP1) (Novus Biologicals, Littleton, CO), and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) (Santa Cruz Biotechnology, Inc. Dallas, TX). Following incubation with IRDye secondary antibodies, proteins were visualized and quantified on a Li-COR imaging system (LI-COR Inc., Lincoln, NE).

Statistical analyses
Data are expressed as mean ± SEM with comparisons carried out using a two-tailed student's t-test for two-group comparisons using Graphpad Prism. p-values < 0.05 were considered significant.
Supporting information S1 Fig. Full length blots


text:
Cancer cell redirection biomarker discovery using a mutual information approach

Introducing tumor-derived cells into normal mammary stem cell niches at a sufficiently high ratio of normal to tumorous cells causes those tumor cells to undergo a change to normal mammary phenotype and yield normal mammary progeny. This phenomenon has been termed cancer cell redirection. We have developed an in vitro model that mimics in vivo redirection of cancer cells by the normal mammary microenvironment. Using the RNA profiling data from this cellular model, we examined high-level characteristics of the normal, redirected, and tumor transcriptomes and found the global expression profiles clearly distinguish the three expression states. To identify potential redirection biomarkers that cause the redirected state to shift toward the normal expression pattern, we used mutual information relationships between normal, redirected, and tumor cell groups. Mutual information relationship analysis reduced a dataset of over 35,000 gene expression measurements spread over 13,000 curated gene sets to a set of 20 significant molecular signatures totaling 906 unique loci. Several of these molecular signatures are hallmark drivers of the tumor state. Using differential expression as a guide, we further refined the gene set to 120 core redirection biomarker genes. The expression levels of these core biomarkers are sufficient to make the normal and redirected gene expression states indistinguishable from each other but radically different from the tumor state.

Introduction
Cancer initiation and progression is a complex genetic disease where mutations and epigenetic alterations in cells lead to inactivation of tumor suppression genes, activation of oncogenes, and impact DNA repair processes [1][2]. The accumulation of genetic mutations often leads to deregulation of proliferative signaling pathways and suppression of pro-differentiation apoptotic pathways. The differential expression of signaling pathways affects not only the mutated cells but also impacts surrounding cells through intercellular communication involving a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 biophysical and biochemical modes of signaling. Intercellular communication is not a onedirection process, as surrounding cells are known to influence tumor cell activity [3].
Normal mammary microenvironments, or somatic stem cell niches, have been shown to direct the cell fates of non-mammary stem cells [4][5][6][7]. When non-mammary stem cells are incorporated into reforming mammary stem cell niches during mammary tissue regeneration the non-mammary stem cells adopt a mammary phenotype and provide progeny to a functional reconstituted mammary gland in vivo. When tumor-derived cells are incorporated into reforming normal mammary stem cell niches the tumor cells also adopt a normal mammary phenotype and provide differentiated cell progeny to the normal mammary outgrowth [8][9][10]. This phenomenon has been termed cancer cell redirection. Cancer cell redirection is determined on the ratio of cancer cells to normal mammary epithelial cells present. Successful redirection of human breast cancer cells and mouse mammary tumor cells occurs at a ratio of 1 cancer cell for every 50 normal epithelial cells while redirection of embryonal testicular carcinoma cells can occur at a ratio of 1 cancer cell for every 10 normal cells. When mouse mammary-tumor derived cells that overexpress erbB2 are redirected, the auto-phosphorylation of the erbB2 tyrosine kinase is attenuated while total expression of erbB2 is not impacted [11]. Reduced erbB2 phosphorylation is one mechanism involved in cancer cell redirection and detection of reduced receptor activity serves as a biomarker of cancer cell redirection.
The genetic profiles of insipient cancer cells change from normal expression patterns to ultimately their cancer cell profile [12]. Breast cancers have been divided into six main groups based on genetic profiles with additional subgroups being added upon discovery of new genetic profiles. The six main groups are 1) Luminal A, 2) Luminal B, 3) HER2 enriched, and 4) claudin low, 5) normal-like, and 6) basal-like [13]. Amplification and overexpression of HER2 is observed in 20-30% of human breast cancers and is inversely correlated with patient survival [14][15][16]. Within these complex differential gene expression patterns lie the causal genetic mechanisms underlying tumorigenesis and possibly cancer cell redirection.
We have developed an in vitro system of cancer cell redirection that employs the 1:50 ratio of erbB2-overexpressing cancer cells to normal cells [11]. This in vitro system has been validated as an alternative to the in vivo model. Using our in vitro system of cancer cell redirection, we investigated the genetic profiles of erbB2-overexpressing mammary tumor-derived cells as they undergo the redirection phenomenon. In this report, we present transcriptome profiling results from multiple mouse sorted cell groups that model normal, redirected, and tumor states. Then we describe the application of a mutual information approach to identify relevant molecular signatures (biomarker packages) that appear to be involved in cancer cell redirection.

Magnetic sorting
The protocol used for magnetic sorting is described elsewhere [8]. After 4 days in culture cells were detached by trypsin, washed once with PBS and resuspended in 100 μl of diluent containing primary antibody (1:50; anti-erbB2, Miltenyi) and incubated for 30 min at 4˚C. The cells were then washed 2 x 10 min and resuspended in 100 μl of diluent containing biotinylated secondary antibody (1:100) and incubated for 15 min at 4˚C. The cells were then washed 2 x 10 min and resuspended in 80:20 μl mix of diluent and anti-biotin magnetic beads (Miltenyi) and incubated for 15 min at 4˚C. The cells were then washed 2 x 10 min and resuspended in 500 μl of running buffer and separated through a LS column (Miltenyi). The erbB2-positive and erbB2-depleted fractions were collected (Fig 1A).

RNA isolation
Total RNA was isolated from the sorted samples using an RNAaqueous Micro kit (Ambion, Austin, TX) that utilizes glass fiber filter column purification. Isolated total RNA was then treated with DNase (Qiagen, Valencia, CA) to remove any DNA contamination. The concentration of RNA was determined using a NanoDrop and the RNA integrity was analyzed with a RNA nano chip on a Bioanalyzer (Agilent Technologies, Santa Clara, CA). Total RNA was isolated from three independent experiments performed sequentially.

qRT-PCR validation
To validate microarray results we selected three genes: AREG, ERBB2, and THBS1 for qRT-PCR analysis. The housekeeping gene GAPDH was used as a reference gene to normalize the expression of each test gene. Primers used for each gene are listed in S2 Table. RNA was reverse-transcribed to cDNA using the Ambion Retroscript kit two-step protocol. The quantity and quality of the RNA was determined using a Nanodrop 2000. The cDNA was analyzed using the QuantiTech SYBR Green RT-PCR Kit (Qiagen, Valencia, CA) on the Step One Plus (Applied Biosystems, Grand Island, NY). Relative expression was determined using the ΔΔCt method with GAPDH as the reference gene. Results of the validation are presented in S1 Fig.

Data analysis
Data was collected as RNA sequence microarray measurements from three repeated experiments involving six cell groups, A-F ( Fig 1A). The RNA normalized gene expression matrix (GEM; available accession # GSE89963) consisted of intensity measurements of 35,556 probe sets for the cell groups, three replicates each of A through F, yielding 18 columns. The range of the data was compressed by log 2 transformation, yielding an expression range from 3.582 to 14.052. All calculations were performed in MATLAB. Mutual information (MI), using units of "bits," was used to describe the similarity of the cell groups to each other and of subsets of genes to each other. Here, the term "information" (or alternatively, "entropy") reflects its usage in information theory, as a measure of uncertainty about a distribution [21]. Mutual information is a method of measuring the symmetric dependence of two variables. It is not dissimilar to Pearson's correlation, in this sense. Unlike Pearson's correlation however, mutual information, defined logarithmically, is not limited in its sensitivity to the measurement of linear relationships between groups. [21]. We utilized an existing MI toolbox for MATLAB [22].

Visualization
Cell groups were visualized using classic multidimensional scaling (CMDS) and the cmdscale function in MATLAB. For this, a dissimilarity matrix (DM) was built based on inverse MI. MI was calculated for each combination of cell group-replicates, column pairs from the gene expression matrix (GEM), and maximum entropy for the set size was divided by this MI value to give a dissimilarity score. CMDS was used to build an approximate picture in 1-dimensional space of the "spread" of the expression profiles for each cell group and later, to visualize the relationship, in 3-dimensional space, of the similarity of the cell groups to each other based on subsets of genes.

Confocal imaging
Cultures were grown on chamber slides and fixed with 4% paraformaldehyde for 10 min at room temperature, rinsed with PBS then stained using standard protocols. Briefly, the fixed cells were permeabilized with 0.1% Triton X-100 then blocked using 10% serum. The primary antibodies used were anti-Mapk1 (1:800), anti-phospho-Neu (1:50)(Santa Cruz Biotech), anti-Notch2 (1:200)(Cell Signaling Technologies); each was applied and incubated overnight at 4˚C. Secondary antibodies were conjugated to Alexa 488 or Alexa 568 (1:200)(Life Technologies) and incubated for 60 min at room temperature. Slides were coverslipped with ProLong Antidfade mounting media containing DAPI (Life Technologies). Images were collected using a Leica TCS SPE confocal microscope at the same laser and acquisition setting. To ensure the laser power and imaging settings were not acquiring autofluoresence, a comparison image was generated from using an unstained sample. Images were analyzed using Image J and Adobe Photoshop.

Western blotting
Protein lysates were collected using M-PER mammalian protein extraction reagent with protease and phosphatase inhibitors added (Thermo Scientific; Rockford, IL). Lysates were cleared at 10,000 rpm for 10 min at 4˚C then transferred to new tubes and frozen at -20˚C until analysis. Protein concentration was determined using a BCA assay. Samples were combined with sample running buffer and boiled for 10 min. Proteins were separated on a 4-20% gel, transferred to nitrocellulose then probed using anti-β-actin and anti-Notch2 followed by HRP-conjugated secondary antibodies (all Cell Signaling Tech). Target proteins were detected using the chemiluminescent reagent Lumiglo (Cell Signaling) and visualized using FluorChemM (Cell Biosciences; Wallingford, CT).

Sample collection
Mammary tumor-derived cells that overexpress erbB2 were co-cultured with normal mammary epithelial cells in our in vitro model of cancer cell redirection. The different ratio cultures were magnetically sorted into erbB2 + and erbB2fractions ( Fig 1A). Each fraction was assigned a Group designation (A-F) (Fig 1A). RNA collected from each fraction was then arrayed. Generated heatmaps of all transcripts are presented in Fig 1B.

MI-based molecular signature discovery
In the interest of exploring the behavior of genes with shared action, 13,311 gene lists, or molecular signatures, from the Broad Institute Molecular Signatures Database were evaluated. To transform the molecular signatures to sets of values from the gene expression matrix (GEM), each signature was translated first into official gene identifiers that were translated into probe set identifiers in the GEM. Not all genes in all molecular signatures were represented in our GEM. This gave each molecular signature represented by an N x 18 expression matrix, a subset of the GEM. Molecular signatures with gene membership N of 10 or fewer were excluded as being too small to demonstrate reliable mutual information (MI) measurements (Fig 2). Only sets of a size equal to or greater than the range of the data were included for consideration. We attempted to extend each molecular signature by inputting the sets into genemania.org and filtering linked genes by genetic, physical, and co-expression gene interactions. The extended molecular signatures sets are available in S3 Table. Molecular signatures that maximized the ratio of MI between normal and redirected cell groups (groups A and E) to MI between redirected and tumor cell groups (E and B) were determined by this equation:

MIðA; EÞ MIðE; BÞ
This ratio was calculated for each molecular signature to build a distribution of such values. A significance threshold was defined using the Bonferroni correction [23]. The molecular signatures were filtered by minimum size and those with MI(A,E)/MI(E,B) of zero were excluded. Of the 13,311 molecular signatures, 12,527 remained after this filtering. Bonferroni correction yielded a significance threshold of 7.983 x 10 −7 . This corresponded to a lowest significant MI ratio value of 5.817. Molecular signatures whose MI ratio values were above or equal to this threshold were selected as pathways statistically significant with respect to tumor cell redirection.

Visualization
Distributions of expression levels for each cell group showed a remarkable pattern (Fig 3A). Tumor cell groups (B, F) generally exhibited a single peak while a weakly bimodal shape characterized the distributions of normal (A, C, D) and redirected (E) cell groups (Fig 3B). Using CMDS, we rendered the distributions in the single dimension of greatest dissimilarity as  New biomarkers for redirected cancer cells calculated by mutual information (Fig 3A). Note the progressive change in distribution shape along this axis.

MI-based molecular signature discovery
Mutual information ratios were of interest because information content increases with set size. By measuring relative relationships in the dataset, we normalized for the effect of set size on the measurements. We were most interested in the Broad molecular signatures that maximized MI(A,E)/MI(E,B)-i.e. those that demonstrated high mutual information between cell groups A and E and low MI between E and B, interpreting these to be pathways that showed similar patterns of expression in A and E (normal and redirected) and dissimilar patterns of expression in E and B (redirected and tumor).
Based on this ratio, molecular signatures above the threshold of significance were identified. Of the molecular signatures evaluated, 20 exceeded this threshold on the upper limit of the distribution. Those molecular signatures, which demonstrate the greatest whole-group transformations in expression of redirected cells along the tumor-to-normal spectrum, are listed in Table 1. MI ratio results for all molecular signatures evaluated are available in S4 Table. Each of the significant molecular signatures was extended with additional interacting genes, associated with those already present in the molecular signature. The additional genes were added on the basis of significant genetic, co-expression, or physical interaction found in the genemania.org database and significant differential gene expression between cell groups A (normal) and E (redirected) from B (tumor). When MI ratios were calculated for these molecular signatures extended with differentially expressed (p<0.0001) interacting genes, the effect was an improvement in MI(A,E)/MI(E,B) in a majority of cases where new genes were incorporated (REACTOME_SOS_MEDIATED_SIGNALLING,  Table. We visualized representative molecular signatures with CMDS at either extreme along the MI(A,E)/MI(E,B) distribution (Fig 4). Molecular signatures with the lowest and highest ratios correspond to signatures that associate with tumor versus normal states.

Discussion
In this report, we describe the transcriptome profiling of in vitro samples modeling normal, tumor, and redirected cellular states. This analysis yielded 32,399 differentially expressed transcripts between the six cell states A-F (adjusted p < 0.0001; S1 Table). Each of these single gene differential expression patterns is interesting and a potential biomarker, especially those transcripts which were significantly different between redirected and tumor states but not between normal and redirected states. However, we found the large number of relevant transcripts to be unwieldy, so we chose to approach the biomarker discovery from a polygenic perspective using curated molecular signature gene sets that were significantly different in terms of mutual information between redirected and tumor states.
On the path to mutual information-based biomarker discovery, we observed that the global gene expression distributions were quite interesting. First, we noticed that the normal/ New biomarkers for redirected cancer cells redirected states demonstrated a bimodal distribution suggesting two distinct expression intensity gene populations (Fig 3A). The bimodal distribution dissolves as the expression state becomes more tumor-like and highly expressed genes shift to a lower expression state. It is possible that this shift is due to an increase in silenced tumor suppressor genes. Second, by determining the distance between global expression distributions with mutual information, we were able to sort the replicate groups into an alignment that satisfies intuition, where normal (A) and redirected (E) states are spatially close to each other but distant from tumor (B) states with some fluctuation in the intermediates, D, C, and F (Fig 3A). Since the global expression patterns were logical, we were confident that we could detect the specific gene sets underlying the states.
An excellent source of interdependent gene sets exists in the Broad Institute's Molecular Signatures (MS) Database. Using the MI(A,E)/MI(E,B) ratio as a metric, we were able to filter over 13,000 MS down to 20-a manageable gene number that still maintains a significant level of the polygenic complexity required for tumorigenesis and presumably cancer cell redirection ( Table 1). The sum of genes in these pathways is a collective biomarker set for cancer cell redirection. While the total unique gene count is high (906 genes), this number can be reduced to core genes that are not differentially expressed in normal (A) and redirected (E) states but are differentially expressed between normal and tumor (B) states and redirected and tumor states (107 genes, adjusted p < 0.0001). These core genes can be extended by the addition of 13 more, identified by on the basis of gene interactions, giving a total 120 of these core biomarkers. The full list of these is available in S6 Table. Thus, we have significantly narrowed the search for genes potentially involved in cancer cell redirection.
Most of the collective function of genes in the 20 signatures make sense in terms of tumor involvement and are candidate effectors for returning a tumor to a normal state. Eight signatures are clearly involved in cancer. One signature is involved in general tumorigenesis (INGA_TP53_ TARGETS; 15 genes) and seven others in specific tumor subtypes: GOTZMANN_EPITHEL IAL_TO_MESENCHYMAL_TRANSITION_UP (66 genes; liver cancer), MOSERLE_IFNA_ RESPONSE (22 genes; ovarian cancer), CROMER_METASTASIS_DN (8 genes; head and neck cancer), BOGNI_TREATMENT_RELATED_MYELOID_LEUKEMIA_DN (28 genes; leukemia), LANDIS_BREAST_CANCER_PROGRESSION_UP (42 genes; breast cancer), HUANG_DASA-TINIB_RESISTANCE_UP (73 genes; breast cancer), and NIKOLSKY_BREAST_CANCER_21-Q22_AMPLICON (13 genes; breast cancer). The latter three signatures are of high interest given the breast cancer model system we are investigating. While a full discussion of this large number of genes is too vast, we discuss two of the significant signatures in detail below.
The SOS mediated signaling molecular signature (REACTOME_SOS_MEDIATED_-SIGNALLING; Table 1) contains a group of genes implicated in the widely investigated Ras-Mek-Erk pathway, a MAPK (mitogen-activated protein kinase) mediated pathway understood to play a role in cell proliferation and survival. Constitutional activation of this pathway, because of mutation, is a feature of many cancers [24][25]. Stimulation by a growth factor of a receptor tyrosine kinase like EGFR or erbB2 enables the subsequent binding of Grb2 and Sos1 to the receptor, beginning a phosphorylation cascade. The finding that the well-characterized Sos-mediated Ras-Mek-Erk pathway, frequently altered in cancer cells, exhibits the most extreme MI ratio is a reasonable result. Many genes showed expression levels that were depressed in tumor cells as compared to normal and redirected samples (Fig 5A). Mapk1 expression was found elevated in Group A and in Group E compared to Group B (Fig 5A). When cultures were examined for Mapk1 we found high Mapk1 expression in Group A normal cells, very little Mapk1 expression in Group B cancer cells, and differential expression in 1:50 co-cultures (Fig 5C). The normal cells continue to express Mapk1 in the 1:50 co-cultures. Cancer cells expressed very little Mapk1 in the 1:50 co-cultures (Fig 5C green arrows). Redirected cancer cells expressed Mapk1 (Fig 5C red arrows) thus confirming the genetic data.
The molecular signature with the third highest MI ratio is the Notch-HLH pathway (REAC-TOME_NOTCH_HLH_TRANSCRIPTION_PATHWAY; Table 1). The Notch family regulates normal development and when expression patterns are altered developmental disorders, tumor initiation, and cancer progression result. In the normal mouse mammary gland, high levels of Notch3 and Notch4 are found in the terminal end buds (TEBs) that are present during ductal morphogenesis [26]. TEBs contain a subpopulation of duct-limited progenitor cells that also give rise to myoepithelial cells. Notch3 also serves as a marker of luminal progenitor cells [27]. Activation of Notch1 results in an expansion of mammary luminal progenitor cells [28]. Notch1 and Notch2 regulate asymmetric division of mammary progenitor cells during pubertal development [29]. Inhibition of Notch1 reduces cancer stem cell function, reduces expression of Notch target genes HES1, HES5 and HEY-L, and reduces the population of CD44 Hi CD24 low , a population identified as cancer stem cells [30][31][32]. Notch1 was not one of New biomarkers for redirected cancer cells the genes identified during analysis (S1 Table). The shift in Notch expression patterns during redirection is not unexpected as the cells are converting from a tumorigenic phenotype to a normal developmental phenotype (Fig 5B). Protein analysis revealed Notch2 expressed by Group A and Group E with lower expression found in Group B (Fig 5D). This result is similar to the genetic expression data (Fig 5B).
Not only are mouse tumor-derived cells susceptible to redirection [8,11] but human breast cancer and embryonic testicular carcinoma cells have been redirected [9][10]. Both human female and male derived cancer cells differentiated into functional breast epithelial cells in response to signals from the normal mouse mammary microenvironment [8][9][10][11]. This suggests that human cancers are reactive to controlling intercellular signals present in developing mammalian tissues. The signaling pathways identified here may also be involved in potential human cancer cell redirection and differentiation.
One limitation of the results outlined within is the presumption that the different behavior between the normal cells, the cancer cells, and the redirected cells is due to the expression of specific genes and RNAs. Multiple studies have demonstrated that RNA expression does not definitively correlate to protein expression. The processes of mRNA decay, translation, and protein degradation are important factors in addition to mRNA transcription in regards to steady-state protein expression [33][34][35][36].
A second limitation of the data presented here is that it is derived from a single cancer cell line. The MMTV-neu mouse model is an accepted model of human HER2 + breast cancer [37]. There are numerous subsets of human breast cancer; the six main groups are 1) Luminal A, 2) Luminal B, 3) HER2 enriched, and 4) claudin low, 5) normal-like, and 6) basal-like [13]. Future studies will examine the profiles of redirected human breast cancer cells in vitro and in vivo. The human basal-like TNBC cell line MDA-MB-231 has been redirected in vivo so the models we use are not species limited [10].
In conclusion, to the best of our knowledge, we provide the first transcriptome profiling of an in vitro model system of cancer cell redirection. Through MI-based gene expression distribution sorting, we observe dramatic differences in global gene expression patterns between normal and tumor states as well as "movement" of intermediate states including cancer cell redirection towards the appropriate state (Fig 6). The twenty core molecular signatures we discovered using the MI-ratio approach are exciting candidate biomarker gene sets that could be controlling cancer cell redirection (Table 1). We are currently porting our system to human and in vivo systems to further delineate the causal genes that could hold the key to the genetic mechanism of cancer cell redirection.