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Supplementary Figure and Table legends

Supplementary Figure S2. Cell proliferation and glycolytic activity upon transient IDH2 overexpression A-B - Quantification of the integrated density of cellROX staining in control and IDH2-overexpressing cells (A) and in the control and IDH2 knockout cells (B) using ImageJ. C -Western blot analysis shows transient overexpression of IDH2 in HCC1500, HCC1954 and in HCC1937 breast cancer cell lines, with GFP overexpression as control. Vinculin serves as loading control. D-F - Transient overexpression of IDH2 does not affect the proliferation rate of the cell lines HCC1954 (D), HCC1500 (E) and HCC1937 (F). G - Re-expression of IDH2 in knockout HCC1143 cells with mCherry (mCh) as control. H - Rescue of sensitivity to oxidative damage in IDH2 knockout cells with re-expression of IDH2. I-K - Increased glucose uptake and lactate secretion, accompanied with elevated extracellular acidification rates measured by Seahorse flux analyzer showed higher glycolytic activity upon transient IDH2 overexpression. (*p-value

Supplementary Table S3: Eigenprotein modules and the metabolic pathway enrichments

Cancer-specific metabolic phenotypes and their vulnerabilities represent a viable area of cancer research. In this study, we explored the association of breast cancer subtypes with different metabolic phenotypes and identified isocitrate dehydrogenase 2 (IDH2) as a key player in triple-negative breast cancer (TNBC) and HER2. Functional assays combined with mass spectrometry–based analyses revealed the oncogenic role of IDH2 in cell proliferation, anchorage-independent growth, glycolysis, mitochondrial respiration, and antioxidant defense. Genome-scale metabolic modeling identified phosphoglycerate dehydrogenase (PHGDH) and phosphoserine aminotransferase (PSAT1) as the synthetic dosage lethal (SDL) partners of IDH2. In agreement, CRISPR-Cas9 knockout of PHGDH and PSAT1 showed the essentiality of serine biosynthesis proteins in IDH2-high cells. The clinical significance of the SDL interaction was supported by patients with IDH2-high/PHGDH-low tumors, who exhibited longer survival than patients with IDH2-high/PHGDH-high tumors. Furthermore, PHGDH inhibitors were effective in treating IDH2-high cells in vitro and in vivo. Altogether, our study creates a new link between two known cancer regulators and emphasizes PHGDH as a promising target for TNBC with IDH2 overexpression.Significance:These findings highlight the metabolic dependence of IDH2 on the serine biosynthesis pathway, adding an important layer to the connection between TCA cycle and glycolysis, which can be translated into novel targeted therapies.

The mTORC1 substrate, S6 Kinase 1 (S6K1), is involved in the regulation of cell growth, ribosome biogenesis, glucose homeostasis, and adipogenesis. Accumulating evidence has suggested a role for mTORC1 signaling in the DNA damage response. This is mostly based on the findings that mTORC1 inhibitors sensitized cells to DNA damage. However, a direct role of the mTORC1-S6K1 signaling pathway in DNA repair and the mechanism by which this signaling pathway regulates DNA repair is unknown. In this study, we discovered a novel role for S6K1 in regulating DNA repair through the coordinated regulation of the cell cycle, homologous recombination (HR) DNA repair (HRR) and mismatch DNA repair (MMR) mechanisms. Here, we show that S6K1 orchestrates DNA repair by phosphorylation of Cdk1 at serine 39, causing G2/M cell cycle arrest enabling homologous recombination and by phosphorylation of MSH6 at serine 309, enhancing MMR. Moreover, breast cancer cells harboringDamage to the DNA in our cells can cause harmful changes that, if unchecked, can lead to the development of cancer. To help prevent this, cellular mechanisms are in place to repair defects in the DNA. A particular process, known as the mTORC1-S6K1 pathway is suspected to be important for repair because when this pathway is blocked, cells become more sensitive to DNA damage. It is still unknown how the various proteins involved in the mTORC1-S6K1 pathway contribute to repairing DNA. One of these proteins, S6K1, is an enzyme involved in coordinating cell growth and survival. The tumor cells in some forms of breast cancer produce more of this protein than normal, suggesting that S6K1 benefits these cells’ survival. However, it is unclear exactly how the enzyme does this. Amar-Schwartz, Ben-Hur, Jbara et al. studied the role of S6K1 using genetically manipulated mouse cells and human cancer cells. These experiments showed that the protein interacts with two other proteins involved in DNA repair and activates them, regulating two different repair mechanisms and protecting cells against damage. These results might explain why some breast cancer tumors are resistant to radiotherapy and chemotherapy treatments, which aim to kill tumor cells by damaging their DNA. If this is the case, these findings could help clinicians choose more effective treatment options for people with cancers that produce additional S6K1. In the future, drugs that block the activity of the enzyme could make cancer cells more susceptible to chemotherapy.

No current screening methods for high-grade ovarian cancer (HGOC) guarantee effective early detection for high-risk women such as germline BRCA mutation carriers. Therefore, the standard-of-care remains risk-reducing salpingo-oophorectomy (RRSO) around age 40. Proximal liquid biopsy is a promising source of biomarkers, but sensitivity has not yet qualified for clinical implementation. We aimed to develop a proteomic assay based on proximal liquid biopsy, as a decision support tool for monitoring high-risk population. Ninety Israeli BRCA1 or BRCA2 mutation carriers were included in the training set (17 HGOC patients and 73 asymptomatic women), (BEDOCA trial; ClinicalTrials.gov Identifier: NCT03150121). The proteome of the microvesicle fraction of the samples was profiled by mass spectrometry and a classifier was developed using logistic regression. An independent cohort of 98 BRCA mutation carriers was used for validation. Safety information was collected for all women who opted for uterine lavage in a clinic setting. We present a 7-protein diagnostic signature, with AUC0.97 and a negative predictive value (NPV) of 100% for detecting HGOC. The AUC of the biomarker in the independent validation set was0.94 and the NPV99%. The sampling procedure was clinically acceptable, with favorable pain scores and safety. We conclude that the acquisition of Müllerian tract proximal liquid biopsies in women at high-risk for HGOC and the application of the BRCA-specific diagnostic assay demonstrates high sensitivity, specificity, technical feasibility and safety. Similar classifier for an average-risk population is warranted.

The fallopian tube secretory epithelial cells (FTSECs) are the cell-of-origin of most high-grade serous ovarian carcinomas (HGSOC). FTSECs are repeatedly exposed to inflammation induced by follicular fluid (FF) that is released with every ovulation cycle throughout a woman’s reproductive years. Uninterrupted ovulation cycles are an established risk factor for HGSOC. Stimuli present in the FF induce an inflammatory environment which may cause DNA damage eventually leading to serous tumorigenesis. With the aim of elucidating possible mechanistic pathways, we established an ‘ex vivo persistent ovulation model’ mimicking the repeated exposure of human benign fallopian tube epithelium (FTE) to FF. We performed mass spectrometry analysis of the secretome of the ex vivo cultures as well as confirmatory targeted expressional and functional analyses. We demonstrated activation of the NF-κB pathway and upregulation of miR-155 following short-term exposure of FTE to human FF. Increased expression of miR-155 was also detected in primary HGSOC tumors compared with benign primary human FTE and corresponded with changes in the expression of miR-155 target genes. The phenotype of miR-155 overexpression in FTSEC cell line is of increased migratory and altered adhesion capacities. Overall, activation of the NF-κB-miR-155 axis in FTE may represent a possible link between ovulation-induced inflammation, DNA damage, and transcriptional changes that may eventually lead to serious carcinogenesis.

High-grade ovarian cancer (HGOC) is the leading cause of mortality from gynecological malignancies, because of diagnosis at a metastatic stage. Current screening options fail to improve mortality because of the absence of early-stage-specific biomarkers. We postulated that a liquid biopsy, such as utero-tubal lavage (UtL), may identify localized lesions better than systemic approaches of serum/plasma analysis. Further, while mutation-based assays are challenged by the rarity of tumor DNA within nonmutated DNA, analyzing the proteomic profile, is expected to enable earlier detection, as it reveals perturbations in both the tumor as well as in its microenvironment. To attain deep proteomic coverage and overcome the high dynamic range of this body fluid, we applied our method for microvesicle proteomics to the UtL samples. Liquid biopsies from HGOC patients (n = 49) and controls (n = 127) were divided into a discovery and validation sets. Data-dependent analysis of the samples on the Q-Exactive mass spectrometer provided depth of 8578 UtL proteins in total, and on average ∼3000 proteins per sample. We used support vector machine algorithms for sample classification, and crossed three feature-selection algorithms, to construct and validate a 9-protein classifier with 70% sensitivity and 76.2% specificity. The signature correctly identified all Stage I lesions. These results demonstrate the potential power of microvesicle-based proteomic biomarkers for early cancer diagnosis.

Cancer-specific metabolic phenotypes and their vulnerabilities represent a viable area of cancer research. In this study, we explored the association of breast cancer subtypes with different metabolic phenotypes and identified isocitrate dehydrogenase 2 (IDH2) as a key player in triple-negative breast cancer (TNBC) and HER2. Functional assays combined with mass spectrometry–based analyses revealed the oncogenic role of IDH2 in cell proliferation, anchorage-independent growth, glycolysis, mitochondrial respiration, and antioxidant defense. Genome-scale metabolic modeling identified phosphoglycerate dehydrogenase (PHGDH) and phosphoserine aminotransferase (PSAT1) as the synthetic dosage lethal (SDL) partners of IDH2. In agreement, CRISPR-Cas9 knockout of PHGDH and PSAT1 showed the essentiality of serine biosynthesis proteins in IDH2-high cells. The clinical significance of the SDL interaction was supported by patients with IDH2-high/PHGDH-low tumors, who exhibited longer survival than patients with IDH2-high/PHGDH-high tumors. Furthermore, PHGDH inhibitors were effective in treating IDH2-high cells in vitro and in vivo. Altogether, our study creates a new link between two known cancer regulators and emphasizes PHGDH as a promising target for TNBC with IDH2 overexpression. Significance: These findings highlight the metabolic dependence of IDH2 on the serine biosynthesis pathway, adding an important layer to the connection between TCA cycle and glycolysis, which can be translated into novel targeted therapies.

Repetitive sequences are hotspots of evolution at multiple levels. However, due to difficulties involved in their assembly and analysis, the role of repeats in tumor evolution is poorly understood. We developed a rigorous motif-based methodology to quantify variations in the repeat content, beyond microsatellites, in proteomes and genomes directly from proteomic and genomic raw data. This method was applied to a wide range of tumors and normal tissues. We identify high similarity between repeat instability patterns in tumors and their patient-matched adjacent normal tissues. Nonetheless, tumor-specific signatures both in protein expression and in the genome strongly correlate with cancer progression and robustly predict the tumorigenic state. In a patient, the hierarchy of genomic repeat instability signatures accurately reconstructs tumor evolution, with primary tumors differentiated from metastases. We observe an inverse relationship between repeat instability and point mutation load within and across patients independent of other somatic aberrations. Thus, repeat instability is a distinct, transient, and compensatory adaptive mechanism in tumor evolution and a potential signal for early detection.

Alternative splicing, a fundamental step in gene expression, is deregulated in many diseases. Splicing factors (SFs), which regulate this process, are up- or down regulated or mutated in several diseases including cancer. To date, there are no inhibitors that directly inhibit the activity of SFs. We designed decoy oligonucleotides, composed of several repeats of a RNA motif, which is recognized by a single SF. Here we show that decoy oligonucleotides targeting splicing factors RBFOX1/2, SRSF1 and PTBP1, can specifically bind to their respective SFs and inhibit their splicing and biological activities both in vitro and in vivo. These decoy oligonucleotides present an approach to specifically downregulate SF activity in conditions where SFs are either up-regulated or hyperactive., Alternative splicing, critical for gene expression, is deregulated in many diseases. Here the authors develop decoy oligonucleotides to specifically downregulate splicing factors activity.

The vast majority of high-grade ovarian cancer (HGOC) patients are diagnosed at a metastatic stage, resulting in exceptionally low cure rates. Current screening options fail to improve mortality due to the absence of early-stage-specific biomarkers and the poor systemic representation of early-stage tumors. We postulated that a gynecologic liquid biopsy, such as utero-tubal lavage (UtL), may identify localized lesions better than systemic approaches of serum/plasma analysis. Furthermore, while mutation-based assays are challenged by the rarity of tumor DNA within nonmutated DNA, analyzing the proteomic profile may potentially enable earlier detection, as it reveals perturbations in both the tumor compartment as well as in its microenvironment. To attain deep proteomic coverage and overcome the high dynamic range of this body fluid, we isolated microvesicles and performed mass spectrometric proteomic analysis of the UtL samples. Liquid biopsies from HGOC patients (n=85), controls (n=183), and healthy BRCA mutation carriers (n=37), were divided into discovery and validation sets. Data-dependent analysis of the samples on the Q-Exactive mass spectrometer provided depth of 8,578 UtL proteins in total, and on average ~3,000 proteins per sample. We used support vector machine algorithms for sample classification, and crossed three feature-selection algorithms, to construct and validate a 9-protein classifier with 63% sensitivity and 73% specificity. The signature correctly identified all Stage I lesions and highlighted increased risk in healthy BRCA carriers. These results demonstrate the potential power of microvesicle-based proteomic biomarkers for early cancer diagnosis but require integration with other biomarker types for improved prediction. Citation Format: Georgina D. Barnabas, Keren Bahar-Shany, Stav Sapoznik, Jacob Korach, Tamar Perri, Eitan Friedman, David Stockheim, Ariella Jakobson-Setton, Ram Eitan, Limor Helpman, Yfat Kadan, Sarit Aviel-Ronen, Michal Harel, Tamar Geiger, Keren Levanon. Proteomic biomarker for detection of ovarian cancer using gynecologic liquid biopsy [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr B06.

The DNA damage response (DDR) is an extensive signaling network that is robustly mobilized by DNA double-strand breaks (DSBs). The primary transducer of the DSB response is the protein kinase, ataxia-telangiectasia, mutated (ATM). Here, we establish nuclear poly(A)-binding protein 1 (PABPN1) as a novel target of ATM and a crucial player in the DSB response. PABPN1 usually functions in regulation of RNA processing and stability. We establish that PABPN1 is recruited to the DDR as a critical regulator of DSB repair. A portion of PABPN1 relocalizes to DSB sites and is phosphorylated on Ser95 in an ATM-dependent manner. PABPN1 depletion sensitizes cells to DSB-inducing agents and prolongs the DSB-induced G2/M cell-cycle arrest, and DSB repair is hampered by PABPN1 depletion or elimination of its phosphorylation site. PABPN1 is required for optimal DSB repair via both nonhomologous end-joining (NHEJ) and homologous recombination repair (HRR), and specifically is essential for efficient DNA-end resection, an initial, key step in HRR. Using mass spectrometry analysis, we capture DNA damage-induced interactions of phospho-PABPN1, including well-established DDR players as well as other RNA metabolizing proteins. Our results uncover a novel ATM-dependent axis in the rapidly growing interface between RNA metabolism and the DDR, Work in Y.S. laboratory is funded by research grants from the Dr Miriam and Sheldon G. Adelson Medical Research Foundation; The A-T Children's Project; The Israel Science Foundation (Joint ISF-NSFC Program with the National Natural Science Foundation of China); The Israel Cancer Research Fund; Work in P.H. lab was supported by R+D+I grant from the Spanish Ministry of Economy and Competitivity [SAF2013-43255-P]; ERC Starting Grant [DSBRECA]; PhD fellowship from the Spanish Ministry of Education (FPU to R.P.-C.); The R.A. lab is supported by NWO grant [NGI 93512001 to R.A.]; The Human Frontier Science Program [LT000640/2013 to A.P.U.]; The work in T.G. lab was supported by The I-CORE Program of the Planning and Budgeting Committee of the Israel Ministry of Education; Y.S. is a Research Professor of the Israel Cancer Research Fund. Funding for open access charge: research grant money.

Introduction Reprogrammed energy metabolism is one among the distinguished cancer hallmarks that unravels the dysregulated bioenergetics of cancer cells. Isocitrate dehydrogenase 2 (IDH2), a mitochondrial metabolic enzyme has been reported to be overexpressed in several cancers, yet the mechanisms of wildtype IDH2-induced transformation are still obscure. We previously identified IDH2, as a novel poor prognosis marker of breast cancer progression. In agreement, transcriptomics (TCGA) and proteomics data of breast cancer clinical samples showed similar expression changes of increased wildtype IDH2 from luminal, to triple-negative and to HER-2 positive, which correlated with tumour aggressiveness. Material and methods We performed intracellular metabolite tracing with heavy labelled glucose (13C6) and glutamine (13C5) followed by ultra-high performance liquid chromatography separation and mass spectrometric analysis on the Q-Exactive Plus instrument. Genome-scale metabolic modelling analysis was performed to identify the IDH2-dependent metabolic genes using Minimization of Metabolic Adjustment (MOMA) algorithm. Results and discussions Overexpression of IDH2 increased serine biosynthesis, increased glycolytic rate and oxidative stress resistance. Genome-scale metabolic modelling of breast cancer tumour data identified dependence on serine biosynthesis as one of the metabolic vulnerability of IDH2 overexpressing cells. CRISPR-Cas9 mediated knockout of phosphoglycerate dehydrogenase (PHGDH) and phosphoserine aminotransferase (PSAT) specifically inhibited IDH2 overexpressing cells, even in the presence of exogenous serine and glycine, and reduced the glycolysis rate and glucose uptake. Furthermore, loss of serine synthesis pathway hampered the flux from glycolysis, into the TCA cycle. Moreover the metabolic perturbations of synthetic dosage lethal partners, PHGDH and PSAT sensitised the IDH2 overexpressing cells to oxidative stress. Conclusion This study reveals WT-IDH2 as a critical metabolic regulator in breast cancer that supports the pro-tumorigenic Warburg effect. These findings may contribute to translate the metabolic dependency to improve targeted therapeutics.

Summary Immunotherapy has revolutionized cancer treatment, yet most patients do not respond. Here, we investigated mechanisms of response by profiling the proteome of clinical samples from advanced stage melanoma patients undergoing either tumor infiltrating lymphocyte (TIL)-based or anti- programmed death 1 (PD1) immunotherapy. Using high-resolution mass spectrometry, we quantified over 10,300 proteins in total and ∼4,500 proteins across most samples in each dataset. Statistical analyses revealed higher oxidative phosphorylation and lipid metabolism in responders than in non-responders in both treatments. To elucidate the effects of the metabolic state on the immune response, we examined melanoma cells upon metabolic perturbations or CRISPR-Cas9 knockouts. These experiments indicated lipid metabolism as a regulatory mechanism that increases melanoma immunogenicity by elevating antigen presentation, thereby increasing sensitivity to T cell mediated killing both in vitro and in vivo. Altogether, our proteomic analyses revealed association between the melanoma metabolic state and the response to immunotherapy, which can be the basis for future improvement of therapeutic response.

The translation machinery and the genes it decodes co-evolved to achieve production throughput and accuracy. Nonetheless, translation errors are frequent, and they affect physiology and protein evolution. Mapping translation errors in proteomes and understanding their causes is hindered by lack of a proteome-wide experimental methodology. We present the first methodology for systematic detection and quantification of errors in entire proteomes. Following proteome mass spectrometry, we identify, in E. coli and yeast, peptides whose mass indicates specific amino acid substitutions. Most substitutions result from codon-anticodon mispairing. Errors occur at sites that evolve rapidly and that minimally affect energetic stability, indicating selection for high translation fidelity. Ribosome density data show that errors occur at sites where ribosome velocity is higher, demonstrating a trade-off between speed and accuracy. Treating bacteria with an aminoglycoside antibiotic or deprivation of specific amino acids resulted in particular patterns of errors. These results reveal a mechanistic and evolutionary basis for translation fidelity.

Background: Current screening programs for early detection of high grade epithelial ovarian cancer (HGOvC) among high-risk populations have failed to show improvement in HGOvC mortality, therefore these women are offered risk-reducing bilateral salpingo-oophorectomy (RRBSO) at 35- 40 years. Stratification of high-risk population, especially BRCA mutation carriers, may enable personalized risk counseling and individualization of timing of RRBSO. In most cases, the precursor lesions of HGOvC arise in the epithelium of the fallopian tube (FT) fimbriae rather than intra-peritoneally. It is therefore plausible that proteins, RNA or DNA from early-stage tumor cells may be identifiable in fluid samples obtained from the lumen of the gynecological tract, thus making it possible to identify curable, early stage lesions. Aims: (1) Test the feasibility of uterine lavage as a minimally invasive test for early detection of ovarian cancer, and (2) Identify novel early-detection biomarkers in the uterine lavage fluid (UtLF). Methods: We developed a method for sampling of gynecologic tract fluid termed uterine lavage fluid (UtLF), which is a simple, reproducible, low-cost office procedure that can be performed routinely during gynecologic follow-up visits. We have already collected UtLF from 140 HGOvC patients and control women undergoing gynecologic surgical procedures for non-malignant indications. Deep proteomic profiling of UtLF is performed by isolation of microparticles from body fluids, followed by solubilization, trypsin digestion and high resolution mass spectrometric (MS) analysis (on the Q-Exactive MS). Machine learning algorithms have been used to extract a classifier that can predict the diagnosis of ovarian cancer. Results: Uterine lavage appears to be a feasible, low burden procedure. The MS approach has identified thousands of proteins in each UtLF specimen, in a high throughput manner. The label-free quantification algorithm (MaxQuant) enables a quantitative comparison between samples from cases and controls. We have derived a 20-protein classifier with an area under the curve (AUC) of Receiver Operating Characteristics (ROC) curve of 0.91 at 20% error. The composite biomarker has been applied to an independent validation set with a negative predictive value (NPV) of 92% and positive predictive value (PPV) of 45%. Conclusions: A minimally invasive technique of uterine lavage to collect unique diagnostic samples, coupled with state-of-the-art proteomics methods, results in a highly sensitive and specific composite biomarker which may be developed in to a screening tool for early detection of serous ovarian cancer in high-risk populations. Citation Format: Keren Bahar-Shany, Georgina D. Barnabas, Limor Helpman, Ariella Yakobson-Siton, Tamar Perri, Ram Eitan, Jacob Korach, Tamar Geiger, Keren Levanon. Minimally invasive test and composite biomarker for early detection of serous ovarian carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 721. doi:10.1158/1538-7445.AM2017-721

Despite the advancements in the cancer therapeutics, gastric cancer ranks as the second most common cancers with high global mortality rate. Integrative functional genomic investigation is a powerful approach to understand the major dysregulations and to identify the potential targets toward the development of targeted therapeutics for various cancers. Intestinal and diffuse type gastric tumors remain the major subtypes and the molecular determinants and drivers of these distinct subtypes remain unidentified. In this investigation, by exploring the network of gene coexpression association in gastric tumors, mRNA expressions of 20,318 genes across 200 gastric tumors were categorized into 21 modules. The genes and the hub genes of the modules show gastric cancer subtype specific expression. The expression patterns of the modules were correlated with intestinal and diffuse subtypes as well as with the differentiation status of gastric tumors. Among these, G1 module has been identified as a major driving force of diffuse type gastric tumors with the features of (i) enriched mesenchymal, mesenchymal stem cell like, and mesenchymal derived multiple lineages, (ii) elevated OCT1 mediated transcription, (iii) involvement of Notch activation, and (iv) reduced polycomb mediated epigenetic repression. G13 module has been identified as key factor in intestinal type gastric tumors and found to have the characteristic features of (i) involvement of embryonic stem cell like properties, (ii) Wnt, MYC and E2F mediated transcription programs, and (iii) involvement of polycomb mediated repression. Thus the differential transcription programs, differential epigenetic regulation and varying stem cell features involved in two major subtypes of gastric cancer were delineated by exploring the gene coexpression network. The identified subtype specific dysregulations could be optimally employed in developing subtype specific therapeutic targeting strategies for gastric cancer.

Genomic aberrations are common in cancers and the long arm of chromosome 1 is known for its frequent amplifications in breast cancer. However, the key candidate genes of 1q, and their contribution in breast cancer pathogenesis remain unexplored. We have analyzed the gene expression profiles of 1635 breast tumor samples using meta-analysis based approach and identified clinically significant candidates from chromosome 1q. Seven candidate genes including exonuclease 1 (EXO1) are consistently over expressed in breast tumors, specifically in high grade and aggressive breast tumors with poor clinical outcome. We derived a EXO1 co-expression module from the mRNA profiles of breast tumors which comprises 1q candidate genes and their co-expressed genes. By integrative functional genomics investigation, we identified the involvement of EGFR, RAS, PI3K/ AKT, MYC, E2F signaling in the regulation of these selected 1q genes in breast tumors and breast cancer cell lines. Expression of EXO1 module was found as indicative of elevated cell proliferation, genomic instability, activated RAS/AKT/MYC/E2F1 signaling pathways and loss of p53 activity in breast tumors. mRNA-drug connectivity analysis indicates inhibition of RAS/PI3K as a possible targeted therapeutic approach for the patients with activated EXO1 module in breast tumors. Thus, we identified seven 1q candidate genes strongly associated with the poor survival of breast cancer patients and identified the possibility of targeting them with EGFR/RAS/PI3K inhibitors. � 2013 Muthuswami et al.