Data pre-processing

Datasets used in the study were collected from original references or microarray repositories Gene Expression Omnibus (GEO), ArrayExpress, etc. The expression profiles taken for the study were normalized while necessary and the expression values were log₂ transformed in the case of single channel data and log ratio data from dual channel data was used as such. The probes were mapped to unique gene symbols with appropriate Affymetrix or Agilent annotation files. The expression values of genes with multiple probes were averaged and used for downstream analysis.

Survival analysis

We considered relapse free survival and overall survival information of the breast cancer patient cohorts for predicting the clinical outcome. Hazard Ratios (HR) and significant p-values were calculated independently for each dataset using coxph function of Survival R package [19,20]. Genes with p-value < 0.005 from Wald statistic were considered significant. Combined HRs for each gene was estimated using inverse variance-weighted method with random effects model. Univariate and Multivariate Cox proportional hazards model for/with other clinical covariates was performed using Rcmdr package [21]. Based on median value of EXO1 gene expression, the samples were stratified into two EXO1+ve and EXO1-ve groups, and are then used as one of the variables for univariate and multivariate analysis.

Kaplan Meier estimate was used for plotting survival curves and p-values were calculated using log-rank test. In case for the EXO1 module, average gene expression values were used for computing survival curve.

Data analysis

EXO1 gene expression values were extracted from normalized log₂ transformed breast tumor profiles. The significant difference in gene expression between any two groups of breast tumor samples were calculated using Student’s t-test (two tailed) and while calculating for more than 2 groups (i.e. for grade), ANOVA was performed.

For defining EXO1 module, the Pearson correlation measure was calculated for each gene – EXO1 pair independently for all the datasets. With an assumption that effect sizes derived from correlation coefficients vary from dataset to dataset, we used random effects model for deriving the weighted average from correlation coefficients of individual datasets. A stringent cut-off of 0.6 and above with p-value<0.001 was fixed in defining the EXO1 module genes. Ontological terms for module genes were given based on DAVID function annotation tool and Cytoscape was used for network visualization [22].

Principal component analysis (PCA) was applied using Rcmdr package from CRAN. Transcription factor binding site analysis for single gene was performed using MAPPER database and for geneset DIRE tool was used. Significant over representation of EXO1 module genes to breast cancer signatures was estimated using hypergeometric distribution function.

Pathway activation analysis

Gene signatures representative of particular phenotype/condition were collected from MsigDB (http://www.broadinstitute.org/gsea/msigdb/genesets.jsp?collection=CGP) or from the original references. Detailed descriptions of the signatures and their sources were provided with Table S3. Each signature represented by corresponding up and down tags were scanned against the gene expression profiles of breast cancer profiles as mentioned earlier [23].

Cell culture

MCF7, T47-D, ZR75, MDA-MB-231, MDA-MB-453, MDA-MB-468, HBL-100 and AGS cells were obtained from National Centre for Cell Sciences (NCCS), Pune, India. Hs578T, Kato III and SKBR-3 were from American Type Culture Collection (ATCC), Manassas, USA. YCC16 cell line was from Yonsei Cancer Centre, Korea [24]. The cells were cultured in the specified media (HiMedia); MCF-7 and YCC16: Minimal Essential Media( MEM), T47-D, ZR 75 & Kato III: RPMI 1640, Hs 578T: DMEM, SK-BR-3 & HBL-100: McCoy’s 5a medium, MDA-MB-231, MDA-MB-453 and MDA-MB-468: Leibovitz, AGS: DMEM-F12, with the supplements L-glutamine (2 mM), sodium pyruvate (1 mM), sodium bicarbonate (1.5 g/L), non-essential amino acids (0.1 mM), penicillin (100 μg/ml), streptomycin (100 μg/ml) (HiMedia) and 10% foetal bovine serum (20 % for Kato III) (Sigma).

Drug Treatment, RT-PCR & Western Blotting

For drug exposure experiments 5x10⁵ cells/well were seeded in a 6-well cell culture dishes. All drug treatments were done upon cells reaching 80 % confluency. For silymarin treatment, the cells were grown in serum-free media for 24 hours prior to drug treatment and treated with 50 μM, 100 μM and 200 μM concentrations. Salirasib was treated at three different concentrations 25 μM, 75 μM and 150 μM. Alkylating agents carboplatin (5, 10 and 15 μg/ml), Cyclophosphamide (2.5, 5 and 10 μM) and Ifosfamide (0.01, 0.05 and 0.1 μg/ml) were used for the treatment in MCF-7 cell lines. All drug treatments were performed for 24 hours and the total RNA was isolated by Trizol (Invitrogen) as per the manufacturer’s protocol. 2 μg of RNA was used to synthesize cDNA using reverse transcriptase (Invitrogen) and the cDNA was used for semi-quantitative PCR analysis. Comparative analysis of the relative expression of EXO1 protein across the panel of breast cancer cell lysates was performed by standard Western blotting using Anti-EXO1 Antibody (LSBIO, LS-B3818 and Sigma, WH0009156M1). 30 μg whole cell lysate were resolved in 12 % gel and 1:100 dilution (LSBIO, LS-B3818) or 1:500 dilution (Sigma, WH0009156M1) of EXO1 antibody was used. Vinculin was probed as loading control for the blotting.

Luciferase Reporter Assays

For luciferase reporter experiments, 75,000 cells/well were seeded in 24-well cell culture dishes. After 24 hours, E2F, MYC, FOXO3 firefly reporter plasmids along with renilla reporter plasmid (SA Biosciences) as internal control in a ratio of 40:1 were transfected using Fugene transfection reagent (Promega). The transfection was performed as per the manufacturer’s instructions. In case of promoter activity assay, E2F or Myc ORF plasmid (Addgene) and EXO1 promoter reporter in the ratio of 1:1 along with renilla reporter plasmid (40:1) was used for transfection. After 48 hours of transfection, the cells were harvested and the luciferase activity was measured using dual luciferase assay protocol [25] in SpectraMax L (Molecular Devices). The normalization was performed by dividing the firefly reporter value by renilla reporter value to obtain relative luciferase activity. Fold change was obtained by dividing the normalized values of the respective pathway reporters with the negative control reporter. Student’s t-test (two tailed) was used for the analysis of significance.

Identification of 1q genes predictive of poor survival in breast tumors

Searching for prevalent genomic amplifications in breast cancers with the genome-wide copy number profiles in progenetix database has shown gain in chromosome 1q as prevalent and occurs in 40 - 50 % of breast cancer patients in multiple cohorts (Figure 1A). Recurrent copy number gain regions in cancer genomes often harbour genes that facilitate tumor development and progression. Despite being the most frequent chromosomal amplification in breast cancer, the candidate cancer genes of 1q amplicon have not been systematically analyzed. By a systematic integrative genomics analysis work-flow (Figure 1B), based on the gene’s association with the survival of breast cancer patients, we short-listed the clinically significant 1q candidate genes. Totally, mRNA expression profiles of 1635 breast tumor samples from 6 independent studies were investigated (Table S1). Cox regression analysis of 498 genes from 1q locus primarily filtered 10 genes that are consistently associated with survival of the patients in at least 3 of the 6 cohorts with the p-value <0.005. The subsequent filtering with the combined p-value <0.005 across 6 datasets, yielded 7 candidate genes ASPM, KIF14, NEK2, DTL, CENPF, CKS1B and EXO1 (Figure 1C) that are significantly associated with poor clinical outcome of the breast cancer patients (Table S2). Since, the physical neighbour genes of a chromosomal locus would sometime have coordinated pattern of expression [26], we mapped the candidate genes to their corresponding genomic location in chromosome 1q and the mapping identified that these genes are not tightly clustered at a specific locus in 1q (Figure 1D). Investigation of the expression pattern of these candidate genes reveals their elevated expression in breast tumor samples when compared to normal breast tissues (Figure 1E). Thus, the frequent 1q amplification, consistent elevated expression of seven 1q genes and their association with poor survival suggests their involvement in breast cancers.

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Figure 1. Identification of genes associated with poor clinical outcome in 1q amplicon of breast tumors.

(A) High frequency amplification of 1q region in multiple cohorts of breast tumors. Graphs I – VI represent inferred copy-number of probes at chromosome 1 from the aCGH studies [61-66]. These graphical representations were the outcome of data visualized through Progenetix [67,68]. Copy number gain and loss are represented with green and red colors respectively. In all these five cohorts, 1q is amplified in 40 - 60 % of tumors. (B) Meta analysis – workflow for the identification 1q genes associated with patient survival. (C) Cox regression coefficient, hazard ratio and p-value of the shortlisted 1q genes, (D) Chromosomal map showing the locations of clinically significant 1q genes. (E) The identified 1q candidate genes showing an elevated expression in breast tumors when compared to the non-cancerous breast tissues in 3 different cohorts.

https://doi.org/10.1371/journal.pone.0077553.g001

Elevated EXO1 expression is associated with poor clinical outcome in breast cancer

While the breast cancer candidacy of CENPF, KIF14, NEK2, DTL, CKS1B, ASPM and EXO1 genes have been identified earlier [27-33], there is only one prominent report indicating the candidacy of EXO1 in breast cancers [33] and remains to be investigated. Apart from the reported polymorphisms [34-36] and elevated expression of EXO1 in Ductal carcinoma in situ [33], also there are contradicting reports relating EXO1 loss of function to increased susceptibility to lymphomas [37], urging the need for further investigation. Therefore, the current identification of the consistently elevated expression of EXO1 gene and its association with poor survival in breast cancers in multiple co-horts is a significant observation. Apart from the identified association between EXO1 expression and poor survival, we further confirmed its clear association with poor clinical outcome using overall survival as end point. Hazard ratio of EXO1 gene expression across 6 independent breast tumor profiles with relapse free survival as endpoint (Figure 2A) and Kaplan Meier survival curves for EXO1 expression with overall survival information as endpoint (Figure 2B-2C) clearly implies the poor clinical outcome associated with higher level EXO1 expression in breast cancer patients. Further, univariate and multivariate Cox proportional hazards model was performed in 3 breast tumor profiles for which maximal clinical variables were available. Univariate analysis revealed the significant association of EXO1 expression with relapse of breast tumors comparable to other individual clinical variables such as age, tumor size, grade, ER status, and lymph node status. In multivariate analysis also EXO1 retained the statistical significance with p-value <0.05 in all 3 analyzed profiles (Table S3). This indicates EXO1 to be an independent predictor of survival, and needs to be investigated in larger cohorts. Since EXO1 expression is associated with the poor prognosis, there arises a question on EXO1 gene expression in the context of specific subtype(s)/group(s) of breast cancers. We addressed this by investigating the expression of EXO1 in 18 breast cancer transcriptome profiles that are available from microarray repositories GEO and Array Express (Table S1). Systematic analysis of EXO1 expression across these breast cancer profiles revealed consistent elevated expression of EXO1 in i) breast tumors when compared to normal breast tissues (Figure S1A), ii) higher grade breast tumors (Figure 2D), iii) ER negative while compared to ER positive tumors (Figure 2E), iv) PR negative subtype of breast tumors (Figure S1B), and v) basal subtype breast tumors when compared to luminal subtypes (Figure S2). We also found subtle elevation of EXO1 expression in invasive ductal breast carcinoma and metastatic breast tumors with modest statistical significance (Figure S1C-S1D). Thus, across multiple cohorts of breast tumors from various populations that were profiled across various microarray platforms, we observed highly consistent and elevated expression of EXO1 in high grade, basal, ER negative and PR negative subtypes. All these show a strong association between EXO1 expression and poor clinical outcome in breast cancer patients.

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Figure 2. EXO1 exhibits elevated expression in high grade and ER negative breast cancers.

(A) Hazard ratio for EXO1 gene expression with relapse free survival as end point in 6 different breast tumor datasets shown as forest plot. B & C) Kaplan Meier curve based on EXO1 gene expression with overall survival as end point in breast tumor profiles, Vijver and GSE7390 respectively. The log-rank test was used for computing significance level for the survival curves. (D) and (E) Comparative analysis of EXO1 gene expression across different grades and subgroups of breast tumors reveal elevated EXO1 expression in high grade (D) and ER negative subgroups of breast tumors (E). The total number of samples in each group is denoted in parenthesis and the GEO accessions of the profiles are shown on the top of each boxplot.

https://doi.org/10.1371/journal.pone.0077553.g002

Identification of the possible upstream regulators of EXO1 in Breast tumors

Elevated expression of EXO1 in breast cancer patients with poor clinical outcome indicates the need for investigating the pathways and factors regulating EXO1 expression. In order to identify the possible upstream regulators of EXO1, gene signature based pathway activation pattern was investigated in the mRNA expression profiles of breast cancer samples. 26 signatures or gene sets representing various pathways and molecular cellular processes were collected from MsigDB and original literatures and used for this analysis (Table S4). Two breast cancer profiles representative of breast tumors [GSE7930], and breast cancer cell lines [E-TABM-157] were analyzed to score the activation of pathway signatures using in-silico gene-set based pathway activation prediction approach described earlier [23,38]. Hierarchical clustering (Figure 3A and Figure S3A), regression analysis (Table S5-S6) and principal component analysis (Figure 3B and Figure S3B) of signature based activation pattern of pathways revealed a significant positive association of EXO1 gene expression with the activation of MYC, RAS, EGFR, Genomic instability, and E2F pathways in breast tumors and cell lines. On the other hand, Estrogen Receptor (ESR1), p53, and BRCA pathways showed negative association with EXO1 expression (Figure 3A - 3B, Figure S3, Table S5-S6). This shows that EGFR, RAS, MYC and E2F1 could be the possible upstream regulators of EXO1.

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Figure 3. Identification of signaling processes associated with EXO1 expression in breast tumors.

(A) The activation status of oncogenic signaling pathways and other cancer signatures in 198 breast tumor samples shown as heatmap. Different pathway or cellular process specific gene-sets were analyzed and the comprehensive activation (red) and inactivation (green) pattern across samples is shown. (B) Principal component analysis of the pathway activation pattern in breast tumors shown in Figure A. (C) Occurrence of E2F, Myc and p53 transcription factor binding sites in EXO1 promoter. (D) Western blot showing the expression of EXO1 in a panel of breast cancer cell lines. (E) RT-PCR showing the expression of EXO1 in a panel of breast cancer cell lines (top panel). In vitro pathway specific reporter assays showing relative activation of Myc and E2F transcription factors in three of the higher level EXO1 expressing cell lines (ER –ve) while compared to two lower level EXO1 expressing cell lines (ER +ve) (Lower panel). These assays have been performed thrice with triplicates. (F) Luciferase reporter assay showing the activation of EXO1 promoter upon the transfection of E2F1 or c-Myc cDNA in MDA-MB231 cells (p-values were 0.013 and 0.009 respectively). pGL3-EXO1 is EXO1 promoter construct in pGL3 enhancer reporter vector. The experiment has been performed thrice with triplicates.

https://doi.org/10.1371/journal.pone.0077553.g003

EXO1 expression is regulated by Myc & E2F transcription factors

In order to identify suitable cell lines for the in vitro experiments, expression of EXO1 across a panel of breast cancer cell lines was probed by western blotting and RT-PCR. Overall, there is a concordance in EXO1 expression pattern identified by Western blotting, RT-PCR and available microarray data (Figure 3D, 3E and Figure S4). Multiple associations indicate the possible regulation of EXO1 by EGFR, RAS, MYC, and E2F1. First, the analysis of transcription factor binding sites in EXO1 promoter region revealed the presence of MYC and E2F1 binding sites (Figure 3C). Second, we investigated the association between EXO1 expression and inherent signalling / transcription factor activity of MYC and E2F transcription factors in a panel of breast cancer cell lines comprising few higher level EXO1 expressing cells (HBL100, SKBR3 and MDA-MB-231) and a couple of lower level EXO1 expressing cells (MCF7 and T47D) by in vitro reporter assay (Figure 3E). In five different breast cancer cell lines, the MYC and E2F reporter plasmids were transfected and assayed for the inherent un-induced transcriptional activity. The normalized luciferase reporter assay result shows a positive association between MYC and E2F reporter activity and EXO1 expression in these cell lines with 5-20 folds higher activation of MYC and E2F in majority of EXO1 expressing cell lines (Figure 3E).

To confirm the MYC and E2F mediated transcriptional regulation of EXO1, -2 kb promoter region of EXO1 was cloned in pGL3-Enhancer reporter vector (designated as pGL3-EXO1). In MDA-MB-231 cells, pGL3-EXO1 was transfected along with MYC and E2F cDNA (ORF cloned in mammalian expression vector) encoding plasmids and assayed for luciferase activity. The results implied a positive regulation of EXO1 promoter by the transcription factors MYC and E2F1 (Figure 3F). Further, chemical inhibition of E2F activity by E2F inhibitor (Silymarin) reduced the expression of EXO1 in MDA-MB-231 cell lines (Figure 4A). All these results demonstrate that MYC and E2F regulates the expression of EXO1 in breast cancer cells.

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Figure 4. In vitro evaluation of Ras, EGFR, and PI3K/AKT pathway mediated regulation of EXO1 expression.

(A - D) Reduced expression of EXO1 in breast cancer cells upon chemical inhibition of E2F, Ras, EGFR, and PI3K/AKT pathways using the specific inhibitors Silymarin, (A) Salirasib (B), Geftinib (C), and LY-294002 (D) respectively. While E2F & Ras inhibition are from MB-231 cells (A-B), PI3K/AKT & EGFR inhibition experiments (C-D) are from MB-468 cells. (E) RT-PCR showing that EXO1 expression is relatively high in gastric cancer cell lines with KRAS mutation, while compared to the cell line without KRAS mutation. (F) FOXO3 reporter assay (inversely proportional to AKT pathway activity) showed relatively higher level activity of AKT in cell lines with higher level EXO1 expression (YCC16 and AGS) compared to the cell line with relatively less folds of AKT activity (Kato III). (G - I) Elevated expression of EXO1 in MCF7 cells upon exposure to DNA damaging agents carboplatin (G), Ifosfamide (H), and Cyclophosphamide (I). The luciferase assays have been performed thrice with triplicates. All semi-quantitative RT-PCRs were performed thrice.

https://doi.org/10.1371/journal.pone.0077553.g004

EGFR and RAS are the upstream regulators of EXO1

Apart from E2F and Myc, EGFR and RAS also showed positive association with the expression of EXO1 in pathway pattern correlation analysis (Figure 3A - 3B). Therefore, we hypothesized RAS being the key downstream regulator of EGFR which in turn might govern the expression of EXO1. In order to investigate this association, we took a KRAS mutant breast cancer cell line, MDA-MB-231 and treated with RAS inhibitor, salirasib. This resulted in the inhibition of EXO1 expression (Figure 4B). Subsequently to address the association between EGFR and EXO1 gene expression, we treated EGFR positive breast cancer cell line, MDA-MB-468, with EGFR inhibitor, gefitinib. As expected, EGFR inhibition resulted in reduced expression of EXO1 in MDA-MB-468, thereby illustrating the involvement of EGFR/RAS cascade in the regulation of EXO1 gene expression in breast cancer cells (Figure 4C). The involvement of RAS/PI3K signalling cascade was confirmed owing to the reduction in EXO1 expression upon treatment with PI3K/AKT inhibitor LY-294002 in the breast cancer cell line MDA-MB-468 (Figure 4D). We also found reduction in the expression of EXO1 upon the same EGFR and PI3K/AKT inhibitor treatment in MDA-MB-231 and ZR-75 cells (data not shown). These show that EXO1 is regulated through RAS/PI3K/AKT signalling in breast cancer cells. Interestingly, even in a panel comprising KRAS mutant and wild type gastric cancer cell lines, EXO1 showed higher expression in KRAS mutant cell lines (YCC16 and AGS) when compared to wild type cells (KATOIII) (Figure 4E). Further, we analyzed the FOXO3 firefly luciferase reporter activity (a negative indicator of RAS/PI3K/AKT pathway activation) in the same gastric cancer cell lines and identified FOXO3 reporter activity to be higher in wild type cells (Kato III) while compared to KRAS mutant cell lines (AGS and YCC16) (Figure 4F). All these indicate that EGFR, Ras, PI3K, Myc, and E2F are involved in the regulation of EXO1. However, among these the direct and indirect regulations remain to be determined.

We also addressed the involvement of EXO1 in DNA repair pathway in cancerous conditions since EXO1 is known to play a vital role in DNA repair process by mismatch mediated repair mechanism [39]. This was addressed by treating MCF7 cell line with different alkylating agents carboplatin, cyclophosphamide and ifosfamide as they are well known to induce DNA repair [40-42]. The experiments showed EXO1’s increased expression with increasing concentration of these alkylating agents in a dose dependent manner thus supporting its role in DNA repair processes (Figure 4G-4I). Apart from DNA repair, another prime factor associated with EXO1 expression is genomic instability (Figure 3A-3B). Since these alkylating agents also would elevate the genomic instability in cancer cells upon exposure [43], these results also indicate that EXO1 expression is indicative of elevated genomic instability in cancer cells.

EXO1 co-expressing genes are predictive of poor clinical outcome in breast cancer patients

Since we identified EXO1 expression as indicative of poor prognosis and genomic instability with activated RAS/PI3K/AKT/MYC/E2F cascade, this observation needs to be explored for possible diagnostic and therapeutic implications. However, rather than single gene, a cluster of genes would be better predictors of a phenotype [44]. Therefore, we derived a set of genes which have the expression pattern very similar to EXO1. Since coexpressing genes would have the same pattern of gene regulation, correlation coefficients of genes coexpressing with EXO1 were computed (Table S7) in 2479 samples from 9 different breast tumor transcriptome profiles (Table S1) and defined a module of genes that are tightly coexpressed with EXO1 in breast tumors (Figure 5A). Further analysis on the features of EXO1 modular genes mirrored EXO1 in i) occurrence of enriched E2F binding sites in the promoter of EXO1 modular genes (Figure S5) and ii) showing significant association with poor survival of the breast cancer patients (Figure 5B-5C). Another striking aspect of EXO1 module is that it includes all seven 1q candidate genes that were originally identified as genes associated with poor survival in breast cancer patients. Analysis of the expression of EXO1 modular genes in a comprehensive panel of 51 breast cancer cell lines showed higher expression in basal and invasive breast cancer cell lines (Figure 5D). EXO1 modular genes showed higher expression in ER negative and higher grade breast tumors (Figure S6). However, a sub-set of ER positive tumors also showed elevated expression of EXO1 modular genes. This shows that EXO1 modular genes are capable of predicting aggressive breast tumors irrespective of ER status.

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Figure 5. EXO1 modular genes are tightly co-expressed and associated with poor prognosis in breast cancer patients

: (A) Identification of EXO1 modular genes using meta-analysis of correlation coefficients from multiple breast tumor datasets. Schematic EXO1 centred network shows that EXO1 co-expressed genes are involved in cell cycle and DNA repair. (B) and (C) Elevated expression of EXO1 modular genes was associated with poor clinical outcome in breast tumor cohorts. (D) Heatmap showing the expression pattern of EXO1 modular genes in 51 breast cancer cell lines. EXO1 modular genes are highly expressed in aggressive and basal cell lines. I-Invasive, N-Non-invasive, B-Basal, L-Luminal and ER status of the cell lines are shown on the top.

https://doi.org/10.1371/journal.pone.0077553.g005

PI3K/AKT inhibition is the potential therapeutic strategy for EXO1 module activated breast tumors

With the identified clinically significant molecular pathological and disease stratification features of EXO1 expression in breast cancer, the identification of suitable therapeutic strategy for targeting the breast cancer cells with elevated EXO1 expression would be useful for the development of novel breast cancer therapeutic options. In breast tumor mRNA profiles (GSE7390), the genes differentially expressed between elevated EXO1 expressing breast tumors (>60%) and reduced EXO1 expressing breast tumors (<10%) were short-listed. The derived genes were analyzed in connectivity map [38] and obtained a list of drugs that could inhibit the expression of genes which are expressed in breast cancer patients with elevated EXO1 expression (Figure 6A). This analysis revealed many PI3K inhibitors like sirolimus, LY-294002, and wortmanin to be potent inhibitors for the potential reversal of the expression of EXO1 associated gene-set (Figure 6B). This is also in agreement with the delineated regulatory mode of EXO1 which involves Ras/PI3K/AKT. In order to further assess this possibility, we analysed the expression of EXO1 modular genes in the gene expression profiles of PI3K / RAS inhibitor treated cells which were readily available in microarray repository. This analysis in a mammary epithelial cell (MCF10A) and few non-breast originated cells (A549 and SHEP), upon treatment with the PI3K inhibitor (LY294002) and Ras inhibitor (FTS), showed tremendous inhibition of EXO1 modular genes (Figure 6C). Similarly, inhibition of Ras by Salirasib also resulted in reduced expression of EXO1 modular and 1q candidate genes NEK2, CKS1B, DTL and KIF14 in MDA-MB-231 cells (Figure 6D). On the other hand, inhibition of PI3K activity in MDA-MB-468 cell lines with LY-294002 also showed decreasing EXO1 expression in a dose dependent manner. All these support Ras/PI3K inhibition as a possible therapeutic strategy for EXO1 modular activated breast tumors.

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Figure 6. Ras/PI3K inhibition is the suitable therapeutic approach for breast tumors with elevated EXO1 modular expression.

(A) Workflow employed for the identification of suitable chemo therapeutic agent for EXO1 module expressing breast tumors. (B) Results of Connectivity map analysis showing that while patients expressing EXO1 co-regulated genes, Pi3K inhibition could be the possible targeted therapeutic approach. (C) Heatmap showing the inhibition of EXO1 modular genes in GSE33403 downloaded from GEO that corresponds to MCF10A cells (PIK3CA E545K mutation) treated with LY294002 for 4 hours and 24 hours. Similarly, the profiles of A549 and SHEP cells treated with the Ras inhibitor FTS were obtained from Blum et al., 2007. (D) RT-PCR showed reduced expression of 5 out of 7, 1q candidate genes NEK2, CKS1B, DTL, KIF14 and EXO1 in MB231 cells upon chemical inhibition of RAS pathway with salirasib.

https://doi.org/10.1371/journal.pone.0077553.g006