The Pandemic Response Commons.

Objectives: A data commons is a software platform for managing, curating, analyzing, and sharing data with a community. The Pandemic Response Commons (PRC) is a data commons designed to provide a data platform for researchers studying an epidemic or pandemic. Methods: The PRC was developed using the open source Gen3 data platform and is based upon consortium, data, and platform agreements developed by the not-for-profit Open Commons Consortium. A formal consortium of Chicagoland area organizations was formed to develop and operate the PRC. Results: The consortium developed a general PRC and an instance of it for the Chicagoland region called the Chicagoland COVID-19 Commons. A Gen3 data platform was set up and operated with policies, procedures, and controls for a NIST SP 800-53 revision 4 Moderate system. A consensus data model for the commons was developed, and a variety of datasets were curated, harmonized and ingested, including statistical summary data about COVID cases, patient level clinical data, and SARS-CoV-2 viral variant data. Discussion and conclusions: Given the various legal and data agreements required to operate a data commons, a PRC is designed to be in place and operating at a low level prior to the occurrence of an epidemic, with the activities increasing as required during an epidemic. A regional instance of a PRC can also be part of a broader data ecosystem or data mesh consisting of multiple regional commons supporting pandemic response through sharing regional data.

Economical Utilization of Health Information with Learning Healthcare System Data Commons.

Finding, accessing, sharing, and analyzing patient data from a clinical setting for collaborative research has continually proven to be a challenge in healthcare organizations. The human and technological architecture required to perform these services exist at the largest academic institutions but are usually under-funded. At smaller, less academically focused healthcare organizations across the United States, where the majority of care is delivered, they are generally absent. Here we propose a solution called the Learning Healthcare System Data Commons where cost is usage-based and the most basic elements are designed to be extensible, allowing it to evolve with the changing landscape of healthcare. Herein we also discuss our reference implementation of this platform tailored specifically for operational sustainability and governance using the data generated in a hospital setting for research, quality, and educational purposes.

Histologic Discordance Between Primary Tumor and Nodal Metastasis in Breast Cancer: Solving a Clinical Conundrum in the Era of Genomics.

Next-generation sequencing (NGS) technologies have become increasingly used for managing breast cancer. In addition to the conventional use of NGS for predicting recurrence risk and identifying potential actionable mutations, NGS can also serve as a powerful tool to understand clonal origin and evolution of tumor pairs and play a unique role in clarifying complex clinical presentations. We report an unusual case of early-stage breast cancer in which the primary tumor and draining axillary node were histologically discordant. The primary tumor was invasive lobular carcinoma, whereas the nodal metastasis was invasive ductal carcinoma. This discordance led us to question whether the tumors had the same origin. NGS performed on both specimens identified no overlapping variants, leading us to conclude that the patient had two separate primary breast cancers, with the nodal tumor representing metastasis from an occult breast cancer. DNA sequencing of the primary tumor and the nodal metastasis allowed us to predict the patient's recurrence risk, and we initiated adjuvant chemotherapy and hormonal therapy based on these results. This case illustrates the utility of NGS for successfully managing a rare and challenging case. KEY POINTS: A degree of molecular concordance is expected for tumors originating from a common stem or progenitor cell. Histological discordance and absence of any genomic overlap should raise suspicion for two separate primary tumors. Paired DNA sequencing of the primary tumor and nodal metastasis can inform clinical decisions when primary breast tumor and axillary metastasis are histologically discordant. Molecular/Precision Oncology Tumor Board is the best setting to facilitate such decisions in these challenging cases. Paired DNA sequencing under these rare circumstances may suggest an occult breast tumor.

Limited inhibition of multiple nodes in a driver network blocks metastasis.

Metastasis suppression by high-dose, multi-drug targeting is unsuccessful due to network heterogeneity and compensatory network activation. Here, we show that targeting driver network signaling capacity by limited inhibition of core pathways is a more effective anti-metastatic strategy. This principle underlies the action of a physiological metastasis suppressor, Raf Kinase Inhibitory Protein (RKIP), that moderately decreases stress-regulated MAP kinase network activity, reducing output to transcription factors such as pro-metastastic BACH1 and motility-related target genes. We developed a low-dose four-drug mimic that blocks metastatic colonization in mouse breast cancer models and increases survival. Experiments and network flow modeling show limited inhibition of multiple pathways is required to overcome variation in MAPK network topology and suppress signaling output across heterogeneous tumor cells. Restricting inhibition of individual kinases dissipates surplus signal, preventing threshold activation of compensatory kinase networks. This low-dose multi-drug approach to decrease signaling capacity of driver networks represents a transformative, clinically relevant strategy for anti-metastatic treatment.

Clinical Course and Factors Associated With Hospitalization and Critical Illness Among COVID-19 Patients in Chicago, Illinois.

BACKGROUND: SARS-CoV-2 is a global pandemic associated with significant morbidity and mortality. However, information from United States cohorts is limited. Understanding predictors of admission and critical illness in these patients is essential to guide prevention and risk stratification strategies. METHODS: This was a retrospective, registry-based cohort study including all patients presenting to Rush University Medical Center in Chicago, Illinois, with COVID-19 from March 4, 2020 to June 21, 2020. Demographic, clinical, laboratory, and treatment data were obtained from the registry and compared between hospitalized and nonhospitalized patients as well as those with critical illness. We used logistic regression modeling to explore risk factors associated with hospitalization and critical illness. RESULTS: A total of 8,673 COVID-19 patients were included in the study, of whom 1,483 (17.1%) were admitted to the hospital and 528 (6.1%) were admitted to the intensive care unit. Risk factors for hospital admission included advanced age, male sex (odds ratio [OR] = 1.69, 95% confidence interval [CI] = 1.44 to 1.98), Hispanic/Latino ethnicity (OR = 1.52, 95% CI = 1.18 to 1.92), hypertension (OR = 1.77, 95% CI = 1.46 to 2.16), diabetes mellitus (OR = 1.84, 95% CI = 1.53 to 2.22), prior CVA (OR = 3.20, 95% CI = 1.99 to 5.14), coronary artery disease (OR = 1.45, 95% CI = 1.03 to 2.06), heart failure (OR = 1.79, 95% CI = 1.23 to 2.61), chronic kidney disease (OR = 2.60, 95% CI = 1.77 to 3.83), end-stage renal disease (OR = 2.22, 95% CI = 1.12 to 4.41), cirrhosis (OR = 2.03, 95% CI = 1.42 to 2.91), fever (OR = 1.43, 95% CI = 1.19 to 1.71), and dyspnea (OR = 4.53, 95% CI = 3.75 to 5.47). Factors associated with critical illness included male sex (OR = 1.45, 95% CI = 1.12 to 1.88), congestive heart failure (OR = 1.45, 95% CI = 1.00 to 2.12), obstructive sleep apnea (OR = 1.58, 95% CI = 1.07 to 2.33), blood-borne cancer (OR = 3.53, 95% CI = 1.26 to 9.86), leukocytosis (OR = 1.53, 95% CI = 1.15 to 2.17), elevated neutrophil-to-lymphocyte ratio (OR = 1.61, 95% CI = 1.20 to 2.17), hypoalbuminemia (OR = 1.80, 95% CI = 1.39 to 2.32), elevated AST (OR = 1.66, 95% CI = 1.20 to 2.29), elevated lactate (OR = 1.95, 95% CI = 1.40 to 2.73), elevated D-Dimer (OR = 1.44, 95% CI = 1.05 to 1.97), and elevated troponin (OR = 3.65, 95% CI = 2.03 to 6.57). CONCLUSION: There are a number of factors associated with hospitalization and critical illness. Clinicians should consider these factors when evaluating patients with COVID-19.

Effective breast cancer combination therapy targeting BACH1 and mitochondrial metabolism.

Mitochondrial metabolism is an attractive target for cancer therapy1,2. Reprogramming metabolic pathways could improve the ability of metabolic inhibitors to suppress cancers with limited treatment options, such as triple-negative breast cancer (TNBC)1,3. Here we show that BTB and CNC homology1 (BACH1)4, a haem-binding transcription factor that is increased in expression in tumours from patients with TNBC, targets mitochondrial metabolism. BACH1 decreases glucose utilization in the tricarboxylic acid cycle and negatively regulates transcription of electron transport chain (ETC) genes. BACH1 depletion by shRNA or degradation by hemin sensitizes cells to ETC inhibitors such as metformin5,6, suppressing growth of both cell line and patient-derived tumour xenografts. Expression of a haem-resistant BACH1 mutant in cells that express a short hairpin RNA for BACH1 rescues the BACH1 phenotype and restores metformin resistance in hemin-treated cells and tumours7. Finally, BACH1 gene expression inversely correlates with ETC gene expression in tumours from patients with breast cancer and in other tumour types, which highlights the clinical relevance of our findings. This study demonstrates that mitochondrial metabolism can be exploited by targeting BACH1 to sensitize breast cancer and potentially other tumour tissues to mitochondrial inhibitors.

Clinical validation of the Tempus xO assay.

We have developed a clinically validated NGS assay that includes tumor, germline and RNA sequencing. We apply this assay to clinical specimens and cell lines, and we demonstrate a clinical sensitivity of 98.4% and positive predictive value of 100% for the clinically actionable variants measured by the assay. We also demonstrate highly accurate copy number measurements and gene rearrangement identification.

Differential expression of circulating biomarkers of tumor phenotype and outcomes in previously treated non-small cell lung cancer patients receiving erlotinib vs. cytotoxic chemotherapy.

BACKGROUND: The objective of this study was to identify serum biomarkers capable of predicting clinical outcomes in previously-treated NSCLC patients with wild-type for EGFR activating mutations or insufficient tissue for mutation status determination. METHODS: Sixty-six Luminex immunoassays representative of biological themes that emerged from a re-analysis of transcriptome data from the Cancer Genome Atlas (TCGA) were evaluate against pretreatment serum specimens from previously-treated advanced NSCLC patients received either cytotoxic chemotherapy (n=32) or erlotinib (n=79). Known EGFR mutation positive cases were excluded from analysis. Associations of biomarkers with outcome parameters and their differential interaction with treatment for survival outcomes were assessed using multivariate Cox PH analyses. RESULTS: Our EMT-based transcriptomic analysis revealed a range of biological processes associated with angiogenesis, apoptosis, cachexia, inflammation, and metabolism emerging as those most highly associated with patient outcome. These processes were evaluated via surrogate serum biomarkers. A treatment-biomarker interaction analysis revealed that higher pretreatment levels of c-Met signaling biomarkers (i.e. HGF levels), pro-inflammatory/ pro-cachexia (e.g. IL-8, sIL-2Rα, FGF-2) processes and a pro-angiogenic (e.g. TGF-α, IL-8, VEGF) milieu were associated with inferior survival (HR=0.35, 0.29, 0.58, 0.50, 0.61, 0.45, respectively; all p<0.05) for patients receiving chemotherapy, relative to erlotinib. In contrast, high levels of decoy receptor for IL-1, sIL-1RII, and a high tissue vimentin/E-cadherin ratio were associated with a poor OS (HR=3.78; p=0.00055) in the erlotinib cohort. CONCLUSIONS: Contemporary precision medicine initiatives that pair patient tumor characteristics with the optimal therapy type may maximize the use of agents targeting EGFR in the treatment of NSCLC.

Gene expression in local stroma reflects breast tumor states and predicts patient outcome.

The surrounding microenvironment has been implicated in the progression of breast tumors to metastasis. However, the degree to which metastatic breast tumors locally reprogram stromal cells as they disrupt tissue boundaries is not well understood. We used species-specific RNA sequencing in a mouse xenograft model to determine how the metastasis suppressor RKIP influences transcription in a panel of paired tumor and stroma tissues. We find that gene expression in metastatic breast tumors is pervasively correlated with gene expression in local stroma of both mouse xenografts and human patients. Changes in stromal gene expression elicited by tumors better predicts subtype and patient survival than tumor gene expression, and genes with coordinated expression in both tissues predict metastasis-free survival. These observations support the use of stroma-based strategies for the diagnosis and prognosis of breast cancer.

Metastasis Suppressors Regulate the Tumor Microenvironment by Blocking Recruitment of Prometastatic Tumor-Associated Macrophages.

Triple-negative breast cancer (TNBC) patients have the highest risk of recurrence and metastasis. Because they cannot be treated with targeted therapies, and many do not respond to chemotherapy, they represent a clinically underserved group. TNBC is characterized by reduced expression of metastasis suppressors such as Raf kinase inhibitory protein (RKIP), which inhibits tumor invasiveness. Mechanisms by which metastasis suppressors alter tumor cells are well characterized; however, their ability to regulate the tumor microenvironment and the importance of such regulation to metastasis suppression are incompletely understood. Here, we use species-specific RNA sequencing to show that RKIP expression in tumors markedly reduces the number and metastatic potential of infiltrating tumor-associated macrophages (TAM). TAMs isolated from nonmetastatic RKIP(+) tumors, relative to metastatic RKIP(-) tumors, exhibit a reduced ability to drive tumor cell invasion and decreased secretion of prometastatic factors, including PRGN, and shed TNFR2. RKIP regulates TAM recruitment by blocking HMGA2, resulting in reduced expression of numerous macrophage chemotactic factors, including CCL5. CCL5 overexpression in RKIP(+) tumors restores recruitment of prometastatic TAMs and intravasation, whereas treatment with the CCL5 receptor antagonist Maraviroc reduces TAM infiltration. These results highlight the importance of RKIP as a regulator of TAM recruitment through chemokines such as CCL5. The clinical significance of these interactions is underscored by our demonstration that a signature comprised of RKIP signaling and prometastatic TAM factors strikingly separates TNBC patients based on survival outcome. Collectively, our findings identify TAMs as a previously unsuspected mechanism by which the metastasis-suppressor RKIP regulates tumor invasiveness, and further suggest that TNBC patients with decreased RKIP activity and increased TAM infiltration may respond to macrophage-based therapeutics.

Mitophagy defects arising from BNip3 loss promote mammary tumor progression to metastasis.

BNip3 is a hypoxia-inducible protein that targets mitochondria for autophagosomal degradation. We report a novel tumor suppressor role for BNip3 in a clinically relevant mouse model of mammary tumorigenesis. BNip3 delays primary mammary tumor growth and progression by preventing the accumulation of dysfunctional mitochondria and resultant excess ROS production. In the absence of BNip3, mammary tumor cells are unable to reduce mitochondrial mass effectively and elevated mitochondrial ROS increases the expression of Hif-1α and Hif target genes, including those involved in glycolysis and angiogenesis­two processes that are also markedly increased in BNip3-null tumors. Glycolysis inhibition attenuates the growth of BNip3-null tumor cells, revealing an increased dependence on autophagy for survival. We also demonstrate that BNIP3 deletion can be used as a prognostic marker of tumor progression to metastasis in human triple-negative breast cancer (TNBC). These studies show that mitochondrial dysfunction­caused by defects in mitophagy­can promote the Warburg effect and tumor progression, and suggest better approaches to stratifying TNBC for treatment.

Network of mutually repressive metastasis regulators can promote cell heterogeneity and metastatic transitions.

The sources and consequences of nongenetic variability in metastatic progression are largely unknown. To address these questions, we characterized a transcriptional regulatory network for the metastasis suppressor Raf kinase inhibitory protein (RKIP). We previously showed that the transcription factor BACH1 is negatively regulated by RKIP and promotes breast cancer metastasis. Here we demonstrate that BACH1 acts in a double-negative (overall positive) feedback loop to inhibit RKIP transcription in breast cancer cells. BACH1 also negatively regulates its own transcription. Analysis of the BACH1 network reveals the existence of an inverse relationship between BACH1 and RKIP involving both monostable and bistable transitions that can potentially give rise to nongenetic variability. Single-cell analysis confirmed monostable and bistable-like behavior. Treatment with histone deacetylase inhibitors or depletion of the polycomb repressor enhancer of zeste homolog 2 altered relative RKIP and BACH1 levels in a manner consistent with a prometastatic state. Together, our results suggest that the mutually repressive relationship between metastatic regulators such as RKIP and BACH1 can play a key role in determining metastatic progression in cancer.

A prognostic gene signature for metastasis-free survival of triple negative breast cancer patients.

Although triple negative breast cancers (TNBC) are the most aggressive subtype of breast cancer, they currently lack targeted therapies. Because this classification still includes a heterogeneous collection of tumors, new tools to classify TNBCs are urgently required in order to improve our prognostic capability for high risk patients and predict response to therapy. We previously defined a gene expression signature, RKIP Pathway Metastasis Signature (RPMS), based upon a metastasis-suppressive signaling pathway initiated by Raf Kinase Inhibitory Protein (RKIP). We have now generated a new BACH1 Pathway Metastasis gene signature (BPMS) that utilizes targets of the metastasis regulator BACH1. Specifically, we substituted experimentally validated target genes to generate a new BACH1 metagene, developed an approach to optimize patient tumor stratification, and reduced the number of signature genes to 30. The BPMS significantly and selectively stratified metastasis-free survival in basal-like and, in particular, TNBC patients. In addition, the BPMS further stratified patients identified as having a good or poor prognosis by other signatures including the Mammaprint® and Oncotype® clinical tests. The BPMS is thus complementary to existing signatures and is a prognostic tool for high risk ER-HER2- patients. We also demonstrate the potential clinical applicability of the BPMS as a single sample predictor. Together, these results reveal the potential of this pathway-based BPMS gene signature to identify high risk TNBC patients that can respond effectively to targeted therapy, and highlight BPMS genes as novel drug targets for therapeutic development.

HMGA2/TET1/HOXA9 signaling pathway regulates breast cancer growth and metastasis.

The ten-eleven translocation (TET) family of methylcytosine dioxygenases initiates demethylation of DNA and is associated with tumorigenesis in many cancers; however, the mechanism is mostly unknown. Here we identify upstream activators and downstream effectors of TET1 in breast cancer using human breast cancer cells and a genetically engineered mouse model. We show that depleting the architectural transcription factor high mobility group AT-hook 2 (HMGA2) induces TET1. TET1 binds and demethylates its own promoter and the promoter of homeobox A (HOXA) genes, enhancing its own expression and stimulating expression of HOXA genes including HOXA7 and HOXA9. Both TET1 and HOXA9 suppress breast tumor growth and metastasis in mouse xenografts. The genes comprising the HMGA2-TET1-HOXA9 pathway are coordinately regulated in breast cancer and together encompass a prognostic signature for patient survival. These results implicate the HMGA2-TET1-HOX signaling pathway in the epigenetic regulation of human breast cancer and highlight the importance of targeting methylation in specific subpopulations as a potential therapeutic strategy.

Incomplete elongation of the chondroitin sulfate linkage region on aggrecan and response to interleukin-1ß.

Aggrecan is the prominent proteoglycan in cartilage and is modified with approximately 100 chondroitin sulfate (CS) chains through a tetrasaccharide linkage structure. In osteoarthritis (OA), the viscoelastic properties of cartilage are compromised on both the quantity and integrity of aggrecan core protein expressed as well as reduced overall CS chain length. Herein, we postulated that chronic low-level inflammation may also contribute to OA progression by promoting regulatory mechanisms in early CS biosynthesis that yield incomplete linkage structures on aggrecan. To test this idea, chondrocytes extracted from human tali were cultured in alginate beads and challenged with 5 ng/mL IL-1ß as a model for chronic inflammation leading to OA progression. Novel mass spectrometry-based methods were devised to detect and quantify partially elongated linkage structures relative to control cultures. The total mole fraction of unelongated xylose residues per aggrecan was significantly less (p = 0.03) after IL-1ß treatment compared to control cultures, with unelongated xylose residues constituting between 6% and 12% of the fraction of total CS measured. A portion (<1%) of the partially elongated linkage structures was found to be either phosphorylated or sulfated. These results establish quantitative mass spectrometry as a very sensitive and effective platform for evaluating truncated proteoglycan linkage structures. Our observations using this method suggest a possible role for aberrant linkage structure elongation in OA progression.

Anti-tumor effects of an engineered "killer" transfer RNA.

A hallmark of cancer cells is their ability to continuously divide; and rapid proliferation requires increased protein translation. Elevating levels of misfolded proteins can elicit growth arrest due to ER stress and decreased global translation. Failure to correct prolonged ER stress eventually results in cell death via apoptosis. tRNA(Ser)(AAU) is an engineered human tRNA(Ser) with an anticodon coding for isoleucine. Here we test the possibility that tRNA(Ser)(AAU) can be an effective killing agent of breast cancer cells and can effectively inhibit tumor-formation in mice. We found that tRNA(Ser)(AAU) exert strong effects on breast cancer translation activity, cell viability, and tumor formation. Translation is strongly inhibited by tRNA(Ser)(AAU) in both tumorigenic and non-tumorigenic cells. tRNA(Ser)(AAU) significantly decreased the number of viable cells over time. A short time treatment with tRNA(Ser)(AAU) was sufficient to eliminate breast tumor formation in a xenograft mouse model. Our results indicate that tRNA(Ser)(AAU) can inhibit breast cancer metabolism, growth and tumor formation. This RNA has strong anti-cancer effects and presents an opportunity for its development into an anti-tumor agent. Because tRNA(Ser)(AAU) corrupts the protein synthesis mechanism that is an integral component of the cell, it would be extremely difficult for tumor cells to evolve and develop resistance against this anti-tumor agent.

RKIP Suppresses Breast Cancer Metastasis to the Bone by Regulating Stroma-Associated Genes.

In the past decade cancer research has recognized the importance of tumorstroma interactions for the progression of primary tumors to an aggressive and invasive phenotype and for colonization of new organs in the context of metastasis. The dialogue between tumor cells and the surrounding stroma is a complex and dynamic phenomenon, as many cell types and soluble factors are involved. While the function of many of the players involved in this cross talk have been studied, the regulatory mechanisms and signaling pathways that control their expression haven't been investigated in depth. By using a novel, interdisciplinary approach applied to the mechanism of action of the metastasis suppressor, Raf kinase inhibitory protein (RKIP), we identified a signaling pathway that suppresses invasion and metastasis through regulation of stroma-associated genes. Conceptually, the approach we developed uses a master regulator and expression arrays from breast cancer patients to formulate hypotheses based on clinical data. Experimental validation is followed by further bioinformatic analysis to establish the clinical significance of discoveries. Using RKIP as an example we show here that this multi-step approach can be used to identify gene regulatory mechanisms that affect tumor-stroma interactions that in turn influence metastasis to the bone or other organs.

Signalling pathway for RKIP and Let-7 regulates and predicts metastatic breast cancer.

Tumour metastasis suppressors are inhibitors of metastasis but their mechanisms of action are generally not understood. We previously showed that the suppressor Raf kinase inhibitory protein (RKIP) inhibits breast tumour metastasis in part via let-7. Here, we demonstrate an integrated approach combining statistical analysis of breast tumour gene expression data and experimental validation to extend the signalling pathway for RKIP. We show that RKIP inhibits let-7 targets (HMGA2, BACH1) that in turn upregulate bone metastasis genes (MMP1, OPN, CXCR4). Our results reveal BACH1 as a novel let-7-regulated transcription factor that induces matrix metalloproteinase1 (MMP1) expression and promotes metastasis. An RKIP pathway metastasis signature (designated RPMS) derived from the complete signalling cascade predicts high metastatic risk better than the individual genes. These results highlight a powerful approach for identifying signalling pathways downstream of a key metastasis suppressor and indicate that analysis of genes in the context of their signalling environment is critical for understanding their predictive and therapeutic potential.

WebaCGH: an interactive online tool for the analysis and display of array comparative genomic hybridisation data.

UNLABELLED: Gene copy number variations occur both in normal cells and in numerous pathologies including cancer and developmental diseases. Array comparative genomic hybridisation (aCGH) is an emerging technology that allows detection of chromosomal gains and losses in a high-resolution format. When aCGH is performed on cDNA and oligonucleotide microarrays, the impact of DNA copy number on gene transcription profiles may be directly compared. We have created an online software tool, WebaCGH, that functions to (i) upload aCGH and gene transcription results from multiple experiments; (ii) identify significant aberrant regions using a local Z-score threshold in user-selected chromosomal segments subjected to smoothing with moving averages; and (iii) display results in a graphical format with full genome and individual chromosome views. In the individual chromosome display, data can be zoomed in/out in both dimensions (i.e. ratio and physical location) and plotted features can have 'mouse over' linking to outside databases to identify loci of interest. Uploaded data can be stored indefinitely for subsequent retrieval and analysis. WebaCGH was created as a Java-based web application using the open-source database MySQL. AVAILABILITY: WebaCGH is freely accessible at http://129.43.22.27/WebaCGH/welcome.htm CONTACT: Xiaolin Wu (forestwu@mail.nih.gov) or Ulises Urzúa (uurzua@med.uchile.cl).

Microarray comparative genomic hybridization profile of a murine model for epithelial ovarian cancer reveals genomic imbalances resembling human ovarian carcinomas.

Microarray comparative genomic hybridization (mCGH) is emerging as a high-resolution technology to detect gene dosage alterations in numerous pathologies, including cancer. We optimized cDNA microarrays to identify genome-wide imbalances in spontaneously transformed mouse ovarian surface epithelial cell lines, an in vitro murine model for ovarian cancer. Amplification of chromosome 19 and a more variable gain pattern of chromosomes 15 and 5 were detected and independently validated using conventional metaphase CGH. In addition, cryptic aberrations in segments of chromosomes 4, 7, 8, 9, 11, 17, and X, allowed identification of 2 related genomic variants among six cell lines studied. Mouse-human synteny revealed an overall early transformation stage with approximately 80% conservation relative to human ovarian malignancies of epithelial origin including low malignant potential tumors, serous carcinoma, and carcinoma cell lines. Importantly, three of the cells bear gained segments 13 and 41 Mbp length of chromosomes 5 and 15, respectively, which are syntenic to human 22q11-13, 8q24 and 12p11-q24, the two latter chromosomal regions thought to define one pathway of karyotypic changes in the development of human ovarian tumors. Our findings support the utility of mouse ovarian surface epithelial (MOSE) cells in studying initiation and progression of human ovarian cancer and as a suitable model to evaluate therapeutic approaches.